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   <news:title>小規模データセットに対するディープニューラルネットワークの強スケーリングの提案（An argument in favor of strong scaling for deep neural networks with small datasets）</news:title>
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   <news:title>皮膚病変分類のためのResidual NetworkとFisher Vectorの統合（Residual Network based Aggregation Model for Skin Lesion Classification）</news:title>
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   <news:title>ヒッグス自然性を問うストップ探索におけるグラフニューラルネットワークの提案（Probing stop pair production at the LHC with graph neural networks）</news:title>
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   <news:title>スケッチから写真風似顔絵を作る新しい直感的ワークフロー（CaricatureShop: Personalized and Photorealistic Caricature Sketching）</news:title>
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   <news:title>ベイズ因子と任意停止の扱い方（Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>皮膚病変のセグメンテーションにおける深層エンコーダ・デコーダネットワーク（ISIC 2017 – Skin Lesion Segmentation Using Deep Encoder-Decoder Network）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>自由ソフトウェア導入戦略が教員養成にもたらす変化（IMPLEMENTATION STRATEGY OF FREE SOFTWARE IN THE PROCESS OF PREPARATION OF TEACHERS OF MATHEMATICS, PHYSICS AND COMPUTER SCIENCE）</news:title>
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   <news:title>電子学習におけるフリーソフトウェアの可能性（Free Software in Electronic Learning for Future Teachers）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>オープンソースで作る電子学習教材（CREATING E-LEARNING MEANS OF FREE SOFTWARE）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>短期かつノイズの多い時系列の不確実性モデリング（Uncertainty Modelling in Deep Networks: Forecasting Short and Noisy Series）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>多段階の文脈統合による肺結節検出の誤検知削減（Multi-Scale Gradual Integration CNN for False Positive Reduction in Pulmonary Nodule Detection）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>大気シャワー物理に深層学習を適用する手法（Deep learning techniques applied to the physics of extensive air showers）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>集合的行列補完（Collective Matrix Completion）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>短い参照音声からの目標話者抽出を可能にするDeep Extractor Network（Deep Extractor Network for Target Speaker Recovery From Single Channel Speech Mixtures）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>ディープCLASSによる皮膚病変分類（Deep-CLASS at ISIC Machine Learning Challenge 2018）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>時空間拡張によるwMEMの応用（SPACE-TIME EXTENSION OF THE MEM APPROACH FOR ELECTROMAGNETIC NEUROIMAGING）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>信頼性コストが生むサンプリングによる確率推論（Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>医用画像におけるインクリメンタル学習とハード・エグザンプル・マイニング（Example Mining for Incremental Learning in Medical Imaging）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Attitude, Aptitude, and Amplitude（Attitude, Aptitude, and Amplitude (AAA): A framework for design driven innovation）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>感情の時間差報酬説（A Temporal Difference Reinforcement Learning Theory of Emotion: unifying emotion, cognition and adaptive behavior）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>異種ラベルを統合して学習する医用画像セグメンテーション（Combining Heterogeneously Labeled Datasets For Training Segmentation Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>工学系大学向け「数学情報学基礎」教育の方法体系モデル（The Model of Methodical System and Learning Objectives of the Foundations of Mathematical Informatics）</news:title>
   <news:publication_date>2026-05-29T13:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>SAAGs: 大規模学習のためのバイアス付き確率的分散削減法（SAAGs: Biased Stochastic Variance Reduction Methods for Large-scale Learning）</news:title>
   <news:publication_date>2026-05-29T13:41:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>残差ネットワークの競合的内画像Squeeze-and-Excitation（Competitive Inner-Imaging Squeeze and Excitation for Residual Network）</news:title>
   <news:publication_date>2026-05-29T13:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Egonetを用いた静的ネットワークの異常検知（Anomaly detection in static networks using egonets）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>意思決定理論に基づく計算創薬におけるモデル評価（A decision theoretic approach to model evaluation in computational drug discovery）</news:title>
   <news:publication_date>2026-05-29T13:40:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Variational Homoencoderの紹介（The Variational Homoencoder: Learning to learn high capacity generative models from few examples）</news:title>
   <news:publication_date>2026-05-29T13:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-29T12:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直感的ファジィ集合アンサンブルに基づく複雑ネットワークの異常検出（Anomaly Detection of Complex Networks Based on Intuitionistic Fuzzy Set Ensemble）</news:title>
   <news:publication_date>2026-05-29T12:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695611</loc>
  <lastmod>2026-05-29T12:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習によるオンラインベイズ回帰の効率化（Meta-Learning Priors for Efficient Online Bayesian Regression）</news:title>
   <news:publication_date>2026-05-29T12:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695609</loc>
  <lastmod>2026-05-29T12:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CLAS12 RICH: ハイブリッド光学で拓くストレンジネス研究（CLAS12 RICH: New Hybrid Geometry for Strangeness Studies）</news:title>
   <news:publication_date>2026-05-29T12:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695607</loc>
  <lastmod>2026-05-29T12:44:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラフィック認識型バックscatter通信が切り拓く低消費電力M2Mの道（Traffic-Aware Backscatter Communications in Wireless-Powered Heterogeneous Networks）</news:title>
   <news:publication_date>2026-05-29T12:44:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695605</loc>
  <lastmod>2026-05-29T12:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己生成ガイダンスによる弱教師付き物体局所化（Self-produced Guidance for Weakly-supervised Object Localization）</news:title>
   <news:publication_date>2026-05-29T12:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695603</loc>
  <lastmod>2026-05-29T12:43:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態空間IsingモデルによるV1ニューロンの相互作用解析（State-space analysis of an Ising model reveals contributions of pairwise interactions to sparseness, fluctuation, and stimulus coding of monkey V1 neurons）</news:title>
   <news:publication_date>2026-05-29T12:43:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695601</loc>
  <lastmod>2026-05-29T12:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模構造化文書の意味理解と表現（Understanding and representing the semantics of large structured documents）</news:title>
   <news:publication_date>2026-05-29T12:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695599</loc>
  <lastmod>2026-05-29T11:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ClusterNet による RGB-D 画像の3Dインスタンスセグメンテーション（ClusterNet: 3D Instance Segmentation in RGB-D Images）</news:title>
   <news:publication_date>2026-05-29T11:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695597</loc>
  <lastmod>2026-05-29T11:51:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダルEEG分類のための深層畳み込み－再帰型ニューラルネットワーク（Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography）</news:title>
   <news:publication_date>2026-05-29T11:51:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695595</loc>
  <lastmod>2026-05-29T11:50:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に大きなモデルを自動分割で学習する仕組み（Supporting Very Large Models using Automatic Dataflow Graph Partitioning）</news:title>
   <news:publication_date>2026-05-29T11:50:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695593</loc>
  <lastmod>2026-05-29T11:50:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変セグメンテーションとU-Netの実務的意義（Lesion segmentation using U-Net network）</news:title>
   <news:publication_date>2026-05-29T11:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695591</loc>
  <lastmod>2026-05-29T11:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイムでエッジを意識した階層的深度推定のためのStereoNet（StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction）</news:title>
   <news:publication_date>2026-05-29T11:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695589</loc>
  <lastmod>2026-05-29T11:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時周波数同時スキャッタリング変換の要点と経営への示唆（Joint Time-Frequency Scattering）</news:title>
   <news:publication_date>2026-05-29T11:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695587</loc>
  <lastmod>2026-05-29T11:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NEESに弱い？ ベイズ最適化でカルマンフィルタ自動調整（Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-29T11:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695585</loc>
  <lastmod>2026-05-29T10:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潤滑剤注入溝の滑り性向上（Enhanced slip properties of lubricant-infused grooves）</news:title>
   <news:publication_date>2026-05-29T10:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695583</loc>
  <lastmod>2026-05-29T10:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的分類と二値データの活用（Hierarchical Classification using Binary Data）</news:title>
   <news:publication_date>2026-05-29T10:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695581</loc>
  <lastmod>2026-05-29T10:57:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RAIMによるICUモニタリングデータ統合の革新（RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data）</news:title>
   <news:publication_date>2026-05-29T10:57:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695579</loc>
  <lastmod>2026-05-29T10:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学空間における応答特性の学習（Operators in Machine Learning: Response Properties in Chemical Space）</news:title>
   <news:publication_date>2026-05-29T10:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695577</loc>
  <lastmod>2026-05-29T10:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>取引記述から送金元金融機関を推定する手法（Identifying Financial Institutions by Transaction Signatures）</news:title>
   <news:publication_date>2026-05-29T10:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695575</loc>
  <lastmod>2026-05-29T10:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学で畳み込みを速める試み：PCNNAによるCNNアクセラレータの概念実証（PCNNA: A Photonic Convolutional Neural Network Accelerator）</news:title>
   <news:publication_date>2026-05-29T10:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695573</loc>
  <lastmod>2026-05-29T10:55:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超広軌道にいる惑星を赤外で探すWEIRD調査（WEIRD: Wide-orbit Exoplanet search with InfraRed Direct imaging）</news:title>
   <news:publication_date>2026-05-29T10:55:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695571</loc>
  <lastmod>2026-05-29T10:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな眼部閉塞における本人性を保った顔再構成（Identity Preserving Face Completion for Large Ocular Region Occlusion）</news:title>
   <news:publication_date>2026-05-29T10:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695569</loc>
  <lastmod>2026-05-29T10:04:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的ニューラルネットワークによる不確実性の扱い（Machine Learning Uncertainties with Adversarial Neural Networks）</news:title>
   <news:publication_date>2026-05-29T10:04:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695567</loc>
  <lastmod>2026-05-29T10:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高等教育におけるモバイル情報・教育環境の構築（The Mobile Information and Educational Environment of Higher Educational Institution）</news:title>
   <news:publication_date>2026-05-29T10:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695565</loc>
  <lastmod>2026-05-29T10:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造認識型近接反復を用いた効率的非凸正則化テンソル補完（Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations）</news:title>
   <news:publication_date>2026-05-29T10:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695563</loc>
  <lastmod>2026-05-29T10:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを含む収束マップからの宇宙論的制約（Cosmological constraints from noisy convergence maps through deep learning）</news:title>
   <news:publication_date>2026-05-29T10:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695561</loc>
  <lastmod>2026-05-29T10:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>研究機関と大学セクターの協働を促すクラウド環境（Collaboration between Research Institutions and University Sector Using Cloud-based Environment）</news:title>
   <news:publication_date>2026-05-29T10:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695559</loc>
  <lastmod>2026-05-29T10:02:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドベース学習環境における電子教材アクセスのハイブリッドサービスモデル（The Hybrid Service Model of Electronic Resources Access in the Cloud-Based Learning Environment）</news:title>
   <news:publication_date>2026-05-29T10:02:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695557</loc>
  <lastmod>2026-05-29T09:10:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波と多波長観測で見つけた新しい天の川銀河の惑星状星雲候補（New Galactic Planetary nebulae selected by radio and multi-wavelength characteristics）</news:title>
   <news:publication_date>2026-05-29T09:10:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695555</loc>
  <lastmod>2026-05-29T09:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古い電力系統に新しい視座を与える：Clarke変換のデータ解析による再解釈（A Data Analytics Perspective of the Clarke and Related Transforms in Power Grid Analysis）</news:title>
   <news:publication_date>2026-05-29T09:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695553</loc>
  <lastmod>2026-05-29T09:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ICT人材育成におけるホリスティックアプローチ（Holistic Approach to Training of ICT Skilled Educational Personnel）</news:title>
   <news:publication_date>2026-05-29T09:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695551</loc>
  <lastmod>2026-05-29T09:09:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NullaNetによるメモリアクセス削減型ニューラル実行（NullaNet: Training Deep Neural Networks for Reduced-Memory-Access Inference）</news:title>
   <news:publication_date>2026-05-29T09:09:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695549</loc>
  <lastmod>2026-05-29T09:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Vadalogによるデータサイエンス: 機械学習と推論の橋渡し（Data Science with Vadalog: Bridging Machine Learning and Reasoning）</news:title>
   <news:publication_date>2026-05-29T09:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695547</loc>
  <lastmod>2026-05-29T09:08:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PS-FCN: 非ランバート面に対応する柔軟な学習フレームワーク（PS-FCN: A Flexible Learning Framework for Photometric Stereo）</news:title>
   <news:publication_date>2026-05-29T09:08:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695545</loc>
  <lastmod>2026-05-29T09:08:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像におけるノイズ注釈の整理手法（Clearing noisy annotations for computed tomography imaging）</news:title>
   <news:publication_date>2026-05-29T09:08:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695543</loc>
  <lastmod>2026-05-29T08:16:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フルイベント解釈（The Full Event Interpretation: An exclusive tagging algorithm for the Belle II experiment）</news:title>
   <news:publication_date>2026-05-29T08:16:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695541</loc>
  <lastmod>2026-05-29T08:15:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソマリ語の人道支援向け自動音声認識（Automatic Speech Recognition for Humanitarian Applications in Somali）</news:title>
   <news:publication_date>2026-05-29T08:15:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/695539</loc>
  <lastmod>2026-05-29T08:15:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対者の行動を学習して秘密通信を実現する（Learning an Adversary’s Actions for Secret Communication）</news:title>
   <news:publication_date>2026-05-29T08:15:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/695537</loc>
  <lastmod>2026-05-29T08:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベアメタルから仮想へ — スーパーコンピューティング機関が初めてクラウドを導入して得た教訓 (From Bare Metal to Virtual: Lessons Learned when a Supercomputing Institute Deploys its First Cloud)</news:title>
   <news:publication_date>2026-05-29T08:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695535</loc>
  <lastmod>2026-05-29T08:15:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenStackとCephを用いた制御付きデータクラウドの構築（Leveraging OpenStack and Ceph for a Controlled-Access Data Cloud）</news:title>
   <news:publication_date>2026-05-29T08:15:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695533</loc>
  <lastmod>2026-05-29T08:15:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼゼロリソース言語のキーワードスポッティングにおけるASR非依存CNN-DTWと多言語ボトルネック特徴（ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages）</news:title>
   <news:publication_date>2026-05-29T08:15:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695531</loc>
  <lastmod>2026-05-29T08:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント強化学習における協調性の定量評価（Measuring Collaborative Emergent Behavior in Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-29T08:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695529</loc>
  <lastmod>2026-05-29T07:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己適応型共鳴イコライゼーション（Auto-adaptive Resonance Equalization using Dilated Residual Networks）</news:title>
   <news:publication_date>2026-05-29T07:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695527</loc>
  <lastmod>2026-05-29T07:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン認識のための適応的判別領域発見（From Volcano to Toyshop: Adaptive Discriminative Region Discovery for Scene Recognition）</news:title>
   <news:publication_date>2026-05-29T07:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695525</loc>
  <lastmod>2026-05-29T07:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる通信ネットワーク遅延のモデル化（Understanding the Modeling of Computer Network Delays using Neural Networks）</news:title>
   <news:publication_date>2026-05-29T07:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695523</loc>
  <lastmod>2026-05-29T07:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル比率から学習する深層学習による肺気腫定量化（Deep Learning from Label Proportions for Emphysema Quantification）</news:title>
   <news:publication_date>2026-05-29T07:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695521</loc>
  <lastmod>2026-05-29T07:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワーク高速化の最近の進展 (Recent Advances in Convolutional Neural Network Acceleration)</news:title>
   <news:publication_date>2026-05-29T07:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695519</loc>
  <lastmod>2026-05-29T07:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離2D文脈を活用した腫瘍セグメンテーションの3D畳み込みニューラルネットワーク（3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context）</news:title>
   <news:publication_date>2026-05-29T07:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695517</loc>
  <lastmod>2026-05-29T07:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調フィルタリングのアルゴリズム選択を変える視点：グラフメタ特徴と多基準メタターゲット（Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets）</news:title>
   <news:publication_date>2026-05-29T07:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695515</loc>
  <lastmod>2026-05-29T06:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視ビューと隠れビューの協調によるマルチビュー・ファジィ分類（Multi-view Fuzzy Classification with Cooperation between Visible and Hidden Views）</news:title>
   <news:publication_date>2026-05-29T06:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695513</loc>
  <lastmod>2026-05-29T06:29:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層対話行為認識（Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations）</news:title>
   <news:publication_date>2026-05-29T06:29:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695511</loc>
  <lastmod>2026-05-29T06:29:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物検索のマルチスケールマッチング（Person Search by Multi-Scale Matching）</news:title>
   <news:publication_date>2026-05-29T06:29:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695509</loc>
  <lastmod>2026-05-29T06:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点画像からのリアルタイム深度推定の要点（MVDepthNet: Real-time Multiview Depth Estimation Neural Network）</news:title>
   <news:publication_date>2026-05-29T06:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695507</loc>
  <lastmod>2026-05-29T06:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高等教育におけるモバイル基盤学習環境での拡張現実（USING TECHNOLOGY OF AUGMENTED REALITY IN A MOBILE-BASED LEARNING ENVIRONMENT OF THE HIGHER EDUCATIONAL INSTITUTION）</news:title>
   <news:publication_date>2026-05-29T06:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695505</loc>
  <lastmod>2026-05-29T06:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMathCloudによる数学・情報学のクラウド学習環境設計（SageMathCloud-based Cloud Learning Environments）</news:title>
   <news:publication_date>2026-05-29T06:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695503</loc>
  <lastmod>2026-05-29T06:27:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不可視ステガノグラフィをGANで実現する手法の要点解説（Invisible Steganography via Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-29T06:27:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695501</loc>
  <lastmod>2026-05-29T05:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STEM教育における人材育成の課題とクラウド基盤学習環境の役割（The Problems of Personnel Training for STEM Education in the Modern Innovative Learning and Research Environment）</news:title>
   <news:publication_date>2026-05-29T05:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695499</loc>
  <lastmod>2026-05-29T05:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学のクラウドベース学習・研究環境の概念、設計原理と実装（The Concept, Principles of Design and Implementation of the University Cloud‑based Learning and Research Environment）</news:title>
   <news:publication_date>2026-05-29T05:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695497</loc>
  <lastmod>2026-05-29T05:35:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stack Neural Module Networksによる説明可能なニューラル計算（Explainable Neural Computation via Stack Neural Module Networks）</news:title>
   <news:publication_date>2026-05-29T05:35:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695495</loc>
  <lastmod>2026-05-29T05:35:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エージェントのためのプログラム可能なゲーム実行基盤（Towards a Programmable Framework for Agent Game Playing）</news:title>
   <news:publication_date>2026-05-29T05:35:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695493</loc>
  <lastmod>2026-05-29T05:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期・長期の時系列推薦における再帰型ニューラルネットワーク（Recurrent Neural Networks for Long and Short-Term Sequential Recommendation）</news:title>
   <news:publication_date>2026-05-29T05:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695491</loc>
  <lastmod>2026-05-29T05:35:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的に細化する無監督画像変換（Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks）</news:title>
   <news:publication_date>2026-05-29T05:35:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695489</loc>
  <lastmod>2026-05-29T05:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復インタラクション学習によるセグメンテーション編集ネットワーク（Iterative Interaction Training for Segmentation Editing Networks）</news:title>
   <news:publication_date>2026-05-29T05:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695487</loc>
  <lastmod>2026-05-29T04:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ間で使える人物再識別の実用的無監督ファインチューニング（Practical Unsupervised Fine-tuning for Person Re-Identification）</news:title>
   <news:publication_date>2026-05-29T04:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695485</loc>
  <lastmod>2026-05-29T04:42:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大面積熱中性子検出器による地下環境の定量測定（A large area detector for thermal neutron ﬂux measurements at the KamLAND site）</news:title>
   <news:publication_date>2026-05-29T04:42:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695483</loc>
  <lastmod>2026-05-29T04:42:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子フィルタに基づく確率的最適化（Particle Filtering Methods for Stochastic Optimization with Application to Large-Scale Empirical Risk Minimization）</news:title>
   <news:publication_date>2026-05-29T04:42:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695481</loc>
  <lastmod>2026-05-29T04:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしクロスドメインマッピングのリスク境界（Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs）</news:title>
   <news:publication_date>2026-05-29T04:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695479</loc>
  <lastmod>2026-05-29T04:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑道路網における交通速度予測にカプセルネットワークを適用する手法（A Capsule Network for Traffic Speed Prediction in Complex Road Networks）</news:title>
   <news:publication_date>2026-05-29T04:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695477</loc>
  <lastmod>2026-05-29T04:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Git Lossによる深層顔認識の識別力向上（Git Loss for Deep Face Recognition）</news:title>
   <news:publication_date>2026-05-29T04:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695475</loc>
  <lastmod>2026-05-29T04:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルチューリングマシンの実装と教訓（Implementing Neural Turing Machines）</news:title>
   <news:publication_date>2026-05-29T04:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695473</loc>
  <lastmod>2026-05-29T03:49:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学術データのための大規模知識グラフ AceKG（AceKG: A Large-scale Knowledge Graph for Academic Data Mining）</news:title>
   <news:publication_date>2026-05-29T03:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695471</loc>
  <lastmod>2026-05-29T03:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変画像分類のための多階層ディープアンサンブル（A Multi-Level Deep Ensemble Model for Skin Lesion Classification in Dermoscopy Images）</news:title>
   <news:publication_date>2026-05-29T03:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695469</loc>
  <lastmod>2026-05-29T03:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D形状をマルチレイヤ高低図として学習する（Learning 3D Shapes as Multi-Layered Height-maps using 2D Convolutional Networks）</news:title>
   <news:publication_date>2026-05-29T03:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695467</loc>
  <lastmod>2026-05-29T03:39:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意誘導型融合ネットワークによる皮膚病変のセグメンテーション（DEEP ATTENTION-GUIDED FUSION NETWORK FOR LESION SEGMENTATION）</news:title>
   <news:publication_date>2026-05-29T03:39:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695465</loc>
  <lastmod>2026-05-29T03:39:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒトの周辺視のぼかしは物体認識に最適か（Human peripheral blur is optimal for object recognition）</news:title>
   <news:publication_date>2026-05-29T03:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695463</loc>
  <lastmod>2026-05-29T03:38:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DASNによるMR脳組織セグメンテーションの精度改善（DASN: Data-Aware Skilled Network for Accurate MR Brain Tissue Segmentation）</news:title>
   <news:publication_date>2026-05-29T03:38:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695461</loc>
  <lastmod>2026-05-29T03:38:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件不変表現によるドメイン一般化 (Domain Generalization via Conditional Invariant Representations)</news:title>
   <news:publication_date>2026-05-29T03:38:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695459</loc>
  <lastmod>2026-05-29T02:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的音声認識におけるゼロショットキーワード検出（Zero-shot keyword spotting for visual speech recognition in the wild）</news:title>
   <news:publication_date>2026-05-29T02:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695457</loc>
  <lastmod>2026-05-29T02:47:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IT専門家教育におけるクラウド技術の活用モデル（Models of using cloud technologies at the IT professionals training）</news:title>
   <news:publication_date>2026-05-29T02:47:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695455</loc>
  <lastmod>2026-05-29T02:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ギャング暴力防止のためのマルチモーダルSNS分析（Multimodal Social Media Analysis for Gang Violence Prevention）</news:title>
   <news:publication_date>2026-05-29T02:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695453</loc>
  <lastmod>2026-05-29T02:46:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号化データで動く深層学習：2P-DNNによるプライバシー保護推論（2P-DNN : Privacy-Preserving Deep Neural Networks Based on Homomorphic Cryptosystem）</news:title>
   <news:publication_date>2026-05-29T02:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695451</loc>
  <lastmod>2026-05-29T02:46:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>研究開発投資は教育を改善するか（More investment in Research and Development for better Education in the future?）</news:title>
   <news:publication_date>2026-05-29T02:46:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695449</loc>
  <lastmod>2026-05-29T02:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LinkNBed: マルチグラフ表現学習とエンティティ連携（LinkNBed: Multi-Graph Representation Learning with Entity Linkage）</news:title>
   <news:publication_date>2026-05-29T02:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695447</loc>
  <lastmod>2026-05-29T02:45:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PongをPolicy Gradientで学習する手法（Learning to Play Pong using Policy Gradient）</news:title>
   <news:publication_date>2026-05-29T02:45:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695445</loc>
  <lastmod>2026-05-29T01:54:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点と直線の位置合わせ：証明可能な近似アルゴリズム（Aligning Points to Lines: Provable Approximations）</news:title>
   <news:publication_date>2026-05-29T01:54:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695443</loc>
  <lastmod>2026-05-29T01:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフレットを数えることで行うネットワーク全体検定（Network Global Testing by Counting Graphlets）</news:title>
   <news:publication_date>2026-05-29T01:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695441</loc>
  <lastmod>2026-05-29T01:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声をそのまま単語に変換する技術の可能性（ACOUSTIC-TO-WORD RECOGNITION WITH SEQUENCE-TO-SEQUENCE MODELS）</news:title>
   <news:publication_date>2026-05-29T01:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695439</loc>
  <lastmod>2026-05-29T01:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付き確率的ブロックモデルの要点（Contextual Stochastic Block Models）</news:title>
   <news:publication_date>2026-05-29T01:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695437</loc>
  <lastmod>2026-05-29T01:52:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域マスクを用いたアクター・アクション意味セグメンテーション（Actor-Action Semantic Segmentation with Region Masks）</news:title>
   <news:publication_date>2026-05-29T01:52:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695435</loc>
  <lastmod>2026-05-29T01:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CPAP流量信号のみで行う睡眠ステージ分類の構造化学習（A Structured Learning Approach with Neural Conditional Random Fields for Sleep Staging）</news:title>
   <news:publication_date>2026-05-29T01:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695433</loc>
  <lastmod>2026-05-29T01:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転遭遇シナリオのクラスタリング（Clustering of Driving Encounter Scenarios Using Connected Vehicle Trajectories）</news:title>
   <news:publication_date>2026-05-29T01:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695431</loc>
  <lastmod>2026-05-29T01:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分データで高速化するMCMCの紹介（Subsampling MCMC - An Introduction for the Survey Statistician）</news:title>
   <news:publication_date>2026-05-29T01:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695429</loc>
  <lastmod>2026-05-29T01:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現動態から遺伝子制御を解読する深層ニューラルネットワーク（Deciphering gene regulation from gene expression dynamics using deep neural network）</news:title>
   <news:publication_date>2026-05-29T01:00:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695427</loc>
  <lastmod>2026-05-29T00:59:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Visual Meshによる定数サンプル密度を用いたリアルタイム物体検出 (Visual Mesh: Real-time Object Detection Using Constant Sample Density)</news:title>
   <news:publication_date>2026-05-29T00:59:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695425</loc>
  <lastmod>2026-05-29T00:59:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GARCHモデルに対するスコア基準の有限標本推論（Score Permutation Based Finite Sample Inference for GARCH Models）</news:title>
   <news:publication_date>2026-05-29T00:59:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695423</loc>
  <lastmod>2026-05-29T00:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整数分解性の予測（PREDICTING THE INTEGER DECOMPOSTION PROPERTY VIA MACHINE LEARNING）</news:title>
   <news:publication_date>2026-05-29T00:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695421</loc>
  <lastmod>2026-05-29T00:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習を用いた皮膚病変セグメンテーションの改善（Improving Automatic Skin Lesion Segmentation using Adversarial Learning based Data Augmentation）</news:title>
   <news:publication_date>2026-05-29T00:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695419</loc>
  <lastmod>2026-05-29T00:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小型および超小型昆虫の羽ばたきパターン変化（Flapping-pattern change in small and very small insects）</news:title>
   <news:publication_date>2026-05-29T00:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695417</loc>
  <lastmod>2026-05-29T00:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PaloBoost: 過学習に強いTreeBoostとOOB正則化手法（PaloBoost: An Overfitting-robust TreeBoost with Out-of-Bag Sample Regularization Techniques）</news:title>
   <news:publication_date>2026-05-29T00:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695415</loc>
  <lastmod>2026-05-29T00:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム2D-3D変形登録と肺放射線治療への応用（Real-Time 2D-3D Deformable Registration with Deep Learning and Application to Lung Radiotherapy Targeting）</news:title>
   <news:publication_date>2026-05-29T00:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695413</loc>
  <lastmod>2026-05-29T00:06:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的DAggerによる安全な模倣学習（EnsembleDAgger: A Bayesian Approach to Safe Imitation Learning）</news:title>
   <news:publication_date>2026-05-29T00:06:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695411</loc>
  <lastmod>2026-05-29T00:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限時間での適応安定化手法（Finite Time Adaptive Stabilization of LQ Systems）</news:title>
   <news:publication_date>2026-05-29T00:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695409</loc>
  <lastmod>2026-05-29T00:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差性に基づく公平性の定義（An Intersectional Definition of Fairness）</news:title>
   <news:publication_date>2026-05-29T00:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695407</loc>
  <lastmod>2026-05-29T00:05:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベースに基づく転移学習の説明手法（Knowledge-based Transfer Learning Explanation）</news:title>
   <news:publication_date>2026-05-29T00:05:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695405</loc>
  <lastmod>2026-05-29T00:04:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシーを守る視覚認識のための敵対的訓練（Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study）</news:title>
   <news:publication_date>2026-05-29T00:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695403</loc>
  <lastmod>2026-05-28T23:13:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manifold learningによるパラメータ削減の実践的意義（Manifold learning for parameter reduction）</news:title>
   <news:publication_date>2026-05-28T23:13:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695401</loc>
  <lastmod>2026-05-28T23:13:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変解析によるメラノーマ検出（Skin Lesion Analysis Towards Melanoma Detection via End-to-end Deep Learning of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-28T23:13:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695399</loc>
  <lastmod>2026-05-28T23:12:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知の把持を新物体に移す手法：能動学習と局所再計画によるグラフトランスファー（Transferring Grasp Configurations using Active Learning and Local Replanning）</news:title>
   <news:publication_date>2026-05-28T23:12:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695397</loc>
  <lastmod>2026-05-28T23:12:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延に敏感なエネルギー収穫ワイヤレスセンサの構造認識強化型強化学習（Accelerated Structure-Aware Reinforcement Learning for Delay-Sensitive Energy Harvesting Wireless Sensors）</news:title>
   <news:publication_date>2026-05-28T23:12:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695395</loc>
  <lastmod>2026-05-28T23:12:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーカー認識の統一ハイパースフィア埋め込み（Unified Hypersphere Embedding for Speaker Recognition）</news:title>
   <news:publication_date>2026-05-28T23:12:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695393</loc>
  <lastmod>2026-05-28T23:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無監督ワイヤレススペクトラム異常検知と可解釈特徴（SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features）</news:title>
   <news:publication_date>2026-05-28T23:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695391</loc>
  <lastmod>2026-05-28T23:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bスプライン曲線近似のための深層学習パラメトリゼーション（Deep Learning Parametrization for B-Spline Curve Approximation）</news:title>
   <news:publication_date>2026-05-28T23:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695389</loc>
  <lastmod>2026-05-28T22:20:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール整列と文脈履歴を用いた注意機構（Multi-scale Alignment and Contextual History for Attention Mechanism in Sequence-to-Sequence Model）</news:title>
   <news:publication_date>2026-05-28T22:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695387</loc>
  <lastmod>2026-05-28T22:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己平衡ロボット制御へのQラーニングと深層Qネットワークの適用（Implementation of Q Learning and Deep Q Network For Controlling a Self Balancing Robot Model）</news:title>
   <news:publication_date>2026-05-28T22:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695385</loc>
  <lastmod>2026-05-28T22:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関ネットによる時空間マルチモーダル学習（Correlation Net: spatiotemporal multimodal deep learning for action recognition）</news:title>
   <news:publication_date>2026-05-28T22:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695383</loc>
  <lastmod>2026-05-28T22:19:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高相関雑音ハイパースペクトル画像のためのTrace Lasso正則化L1ノルムグラフカット（A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image）</news:title>
   <news:publication_date>2026-05-28T22:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695381</loc>
  <lastmod>2026-05-28T22:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画分類のための深層識別モデル（Deep Discriminative Model for Video Classification）</news:title>
   <news:publication_date>2026-05-28T22:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695379</loc>
  <lastmod>2026-05-28T22:18:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅層での深層学習：非専門家向けマルウェア分類（Deep learning at the shallow end: Malware classification for non-domain experts）</news:title>
   <news:publication_date>2026-05-28T22:18:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695377</loc>
  <lastmod>2026-05-28T22:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手と物の操作を文脈で理解する手法（Understanding hand-object manipulation by modeling the contextual relationship between actions, grasp types and object attributes）</news:title>
   <news:publication_date>2026-05-28T22:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695375</loc>
  <lastmod>2026-05-28T21:27:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>購入意図予測：再帰型ニューラルネットワークによる自動特徴学習（Predicting purchasing intent: Automatic Feature Learning using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-28T21:27:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695373</loc>
  <lastmod>2026-05-28T21:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>隠れた非線形動態を分布データから学ぶ（Learning Deep Hidden Nonlinear Dynamics from Aggregate Data）</news:title>
   <news:publication_date>2026-05-28T21:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695371</loc>
  <lastmod>2026-05-28T21:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼カメラだけで現実環境を飛ぶ方法（NAVREN-RL: Learning to fly in real environment via end-to-end deep reinforcement learning using monocular images）</news:title>
   <news:publication_date>2026-05-28T21:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695369</loc>
  <lastmod>2026-05-28T21:17:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速自律車両制御の視覚的手法（Rapid Autonomous Car Control based on Spatial and Temporal Visual Cues）</news:title>
   <news:publication_date>2026-05-28T21:17:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695367</loc>
  <lastmod>2026-05-28T21:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidマルウェア検出の持続可能性に関する予備研究（A Preliminary Study On the Sustainability of Android Malware Detection）</news:title>
   <news:publication_date>2026-05-28T21:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695365</loc>
  <lastmod>2026-05-28T21:16:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>余剰度の段階的増重を用いた相互情報量ベースの特徴選択によるランサムウェア早期検知（Redundancy Coefficient Gradual Up-weighting-based Mutual Information Feature Selection Technique for Crypto-ransomware Early Detection）</news:title>
   <news:publication_date>2026-05-28T21:16:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695363</loc>
  <lastmod>2026-05-28T21:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sign‑Perturbed Sums による有限サンプルでの厳密信頼領域構築（Sign‑Perturbed Sums: A New System Identification Approach for Constructing Exact Non‑Asymptotic Confidence Regions in Linear Regression Models）</news:title>
   <news:publication_date>2026-05-28T21:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695361</loc>
  <lastmod>2026-05-28T20:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lebesgue積分求積法による結合確率分布の数値推定（On Numerical Estimation of Joint Probability Distribution from Lebesgue Integral Quadratures）</news:title>
   <news:publication_date>2026-05-28T20:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695359</loc>
  <lastmod>2026-05-28T20:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極限的RN‑AdSブラックホール上の深部非弾性散乱（Deep Inelastic Scattering on an Extremal RN‑AdS Black Hole）</news:title>
   <news:publication_date>2026-05-28T20:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695357</loc>
  <lastmod>2026-05-28T20:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模化を目指すニューラル定理証明（Towards Neural Theorem Proving at Scale）</news:title>
   <news:publication_date>2026-05-28T20:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695355</loc>
  <lastmod>2026-05-28T20:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散共進化型GANの可能性（Towards Distributed Coevolutionary GANs）</news:title>
   <news:publication_date>2026-05-28T20:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695353</loc>
  <lastmod>2026-05-28T20:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の最近の進展（Recent Advances in Deep Learning: An Overview）</news:title>
   <news:publication_date>2026-05-28T20:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695351</loc>
  <lastmod>2026-05-28T20:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化された画像処理に対するデカップル学習（Decouple Learning for Parameterized Image Operators）</news:title>
   <news:publication_date>2026-05-28T20:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695349</loc>
  <lastmod>2026-05-28T20:13:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帰納的視覚局所化：反復で長い列に強くなる学習法（Inductive Visual Localisation: Factorised Training for Superior Generalisation）</news:title>
   <news:publication_date>2026-05-28T20:13:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695347</loc>
  <lastmod>2026-05-28T19:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークにおける空間相関と値予測（Spatial Correlation and Value Prediction in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-28T19:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695345</loc>
  <lastmod>2026-05-28T19:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データ向け線形時間の密度ベースクラスタリング（Linear density-based clustering with a discrete density model）</news:title>
   <news:publication_date>2026-05-28T19:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695343</loc>
  <lastmod>2026-05-28T19:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率的な適応送信法（Energy-Efﬁcient Adaptive Transmission in Machine Type Communications with Delay-Outage Constraints）</news:title>
   <news:publication_date>2026-05-28T19:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695341</loc>
  <lastmod>2026-05-28T19:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>何がどこにあるかを学べない課題（What is not where: the challenge of integrating spatial representations into deep learning architectures）</news:title>
   <news:publication_date>2026-05-28T19:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695339</loc>
  <lastmod>2026-05-28T19:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴ピラミッドと画像ピラミッドを統合した肺結節検出器（Integrating Feature and Image Pyramid: A Lung Nodule Detector Learned in Curriculum Fashion）</news:title>
   <news:publication_date>2026-05-28T19:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695337</loc>
  <lastmod>2026-05-28T19:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワーク最適化における勾配降下軌道の解析（On the Analysis of Trajectories of Gradient Descent in the Optimization of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-28T19:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695335</loc>
  <lastmod>2026-05-28T19:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム初期化U-netの後処理で白質高信号領域（White Matter Hyperintensity）セグメンテーションを改善する手法（A post-processing method to improve the white matter hyperintensity segmentation accuracy for randomly-initialized U-net）</news:title>
   <news:publication_date>2026-05-28T19:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695333</loc>
  <lastmod>2026-05-28T18:29:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュラー機構的ネットワーク：機構モデルと現象モデルを橋渡しする深層ニューラルネットワーク（Modular Mechanistic Networks: On Bridging Mechanistic and Phenomenological Models with Deep Neural Networks in Natural Language Processing）</news:title>
   <news:publication_date>2026-05-28T18:29:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695331</loc>
  <lastmod>2026-05-28T18:28:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型フェデレーテッド学習で実現するV2V向け超高信頼低遅延通信（Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications）</news:title>
   <news:publication_date>2026-05-28T18:28:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695329</loc>
  <lastmod>2026-05-28T18:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種センサ間の非教師付き変化検出のための結合辞書学習（Coupled dictionary learning for unsupervised change detection between multi-sensor remote sensing images）</news:title>
   <news:publication_date>2026-05-28T18:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695327</loc>
  <lastmod>2026-05-28T18:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時敵対的訓練――他者の失敗から学ぶ（Simultaneous Adversarial Training - Learn from Others’ Mistakes）</news:title>
   <news:publication_date>2026-05-28T18:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695325</loc>
  <lastmod>2026-05-28T18:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-28T18:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695323</loc>
  <lastmod>2026-05-28T18:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚鏡画像分類のための複数畳み込みニューラルネットワーク（Multiple Convolutional Neural Network for Skin Dermoscopic Image Classification）</news:title>
   <news:publication_date>2026-05-28T18:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695321</loc>
  <lastmod>2026-05-28T18:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conditional Infill GANによるマンモグラム分類のデータ増強（Conditional Infill GANs for Data Augmentation in Mammogram Classification）</news:title>
   <news:publication_date>2026-05-28T18:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695319</loc>
  <lastmod>2026-05-28T17:36:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声上の単語を音と意味で埋め込む技術（PHONETIC-AND-SEMANTIC EMBEDDING OF SPOKEN WORDS WITH APPLICATIONS IN SPOKEN CONTENT RETRIEVAL）</news:title>
   <news:publication_date>2026-05-28T17:36:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695317</loc>
  <lastmod>2026-05-28T17:35:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線通信における最適資源配分の学習（Learning Optimal Resource Allocations in Wireless Systems）</news:title>
   <news:publication_date>2026-05-28T17:35:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695315</loc>
  <lastmod>2026-05-28T17:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制限付き強凸関数のためのストリーミング手法（Streaming Methods for Restricted Strongly Convex Functions with Applications to Prototype Selection）</news:title>
   <news:publication_date>2026-05-28T17:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695313</loc>
  <lastmod>2026-05-28T17:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦は検索か、それとも別物か（A Line in the Sand: Recommendation or Ad-hoc Retrieval?）</news:title>
   <news:publication_date>2026-05-28T17:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695311</loc>
  <lastmod>2026-05-28T17:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なオプション批評の学習（Safe Option-Critic: Learning Safety in the Option-Critic Architecture）</news:title>
   <news:publication_date>2026-05-28T17:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695309</loc>
  <lastmod>2026-05-28T17:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ELICA: 要件関連情報を動的に抽出する自動支援ツール（ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information）</news:title>
   <news:publication_date>2026-05-28T17:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695307</loc>
  <lastmod>2026-05-28T17:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習で論理解法の勘どころを学ばせる（LEARNING HEURISTICS FOR QUANTIFIED BOOLEAN FORMULAS THROUGH REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-05-28T17:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695305</loc>
  <lastmod>2026-05-28T16:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク圧縮のためのフィルタ蒸留（Filter Distillation for Network Compression）</news:title>
   <news:publication_date>2026-05-28T16:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695303</loc>
  <lastmod>2026-05-28T16:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Baidu Apollo EMモーションプランナー（Baidu Apollo EM Motion Planner）</news:title>
   <news:publication_date>2026-05-28T16:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695301</loc>
  <lastmod>2026-05-28T16:41:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピースワイズ線形構造を利用する高速で原理的なワーキングセットアルゴリズム（A Fast, Principled Working Set Algorithm for Exploiting Piecewise Linear Structure in Convex Problems）</news:title>
   <news:publication_date>2026-05-28T16:41:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695299</loc>
  <lastmod>2026-05-28T16:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CFHTをMSEへ改築する概念設計（Transforming the Canada France Hawaii Telescope (CFHT) into the Maunakea Spectroscopic Explorer (MSE): A Conceptual Observatory Building and Facilities Design）</news:title>
   <news:publication_date>2026-05-28T16:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695297</loc>
  <lastmod>2026-05-28T16:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メラノーマ分類のための深層学習特徴量アンサンブル（Ensemble of Deep Learned Features for Melanoma Classification）</news:title>
   <news:publication_date>2026-05-28T16:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695295</loc>
  <lastmod>2026-05-28T16:41:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>signProx による1ビット近接最適化の実用性（signProx: One-Bit Proximal Algorithm for Nonconvex Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-28T16:41:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695293</loc>
  <lastmod>2026-05-28T16:40:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃下における頑健で回復力のある信号再構成（Robust Resilient Signal Reconstruction under Adversarial Attacks）</news:title>
   <news:publication_date>2026-05-28T16:40:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695291</loc>
  <lastmod>2026-05-28T15:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書コンテキストを用いたSeq2Seqによる要約（Abstractive and Extractive Text Summarization using Document Context Vector and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-28T15:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695289</loc>
  <lastmod>2026-05-28T15:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークを逆問題とスパース表現で読み解く（Convolutional Neural Networks Analyzed via Inverse Problem Theory and Sparse Representations）</news:title>
   <news:publication_date>2026-05-28T15:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695287</loc>
  <lastmod>2026-05-28T15:49:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Prior Convictionsを利用したブラックボックス敵対的攻撃の効率化（Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors）</news:title>
   <news:publication_date>2026-05-28T15:49:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695285</loc>
  <lastmod>2026-05-28T15:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重みを三値化して精度を保つCNN最適化（Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy）</news:title>
   <news:publication_date>2026-05-28T15:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695283</loc>
  <lastmod>2026-05-28T15:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未来のセマンティックセグメンテーション（Future Semantic Segmentation with Convolutional LSTM）</news:title>
   <news:publication_date>2026-05-28T15:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695281</loc>
  <lastmod>2026-05-28T15:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な局所特徴検出器評価の新基準（Large scale evaluation of local image feature detectors on homography datasets）</news:title>
   <news:publication_date>2026-05-28T15:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695279</loc>
  <lastmod>2026-05-28T15:48:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VC次元の最適境界の解明（Optimal Bounds on the VC-dimension）</news:title>
   <news:publication_date>2026-05-28T15:48:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695277</loc>
  <lastmod>2026-05-28T14:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アップリフトブースティングによる因果効果推定（Boosting for Uplift Modeling）</news:title>
   <news:publication_date>2026-05-28T14:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695275</loc>
  <lastmod>2026-05-28T14:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高密度2値ハイパーディメンショナル計算のハードウェア最適化（Hardware Optimizations of Dense Binary Hyperdimensional Computing）</news:title>
   <news:publication_date>2026-05-28T14:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695273</loc>
  <lastmod>2026-05-28T14:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復重み付き最小二乗法のカウント実験への適用（Application of the Iterated Weighted Least-Squares Fit to counting experiments）</news:title>
   <news:publication_date>2026-05-28T14:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695271</loc>
  <lastmod>2026-05-28T14:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力を学習するグレイボックスファジング（Learning Inputs in Greybox Fuzzing）</news:title>
   <news:publication_date>2026-05-28T14:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695269</loc>
  <lastmod>2026-05-28T14:54:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼ最適な近似・適応性・クエリ複雑性を持つ部分モジュラ最大化（Submodular Maximization with Nearly Optimal Approximation, Adaptivity and Query Complexity）</news:title>
   <news:publication_date>2026-05-28T14:54:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695267</loc>
  <lastmod>2026-05-28T14:54:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の人物を無教師データから学ぶベイズ的アプローチ（From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data）</news:title>
   <news:publication_date>2026-05-28T14:54:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695265</loc>
  <lastmod>2026-05-28T14:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半生成モデルによる共変量シフト適応（Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features）</news:title>
   <news:publication_date>2026-05-28T14:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695263</loc>
  <lastmod>2026-05-28T14:02:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声映像表現を敵対的に分離して生成する話す顔（Talking Face Generation by Adversarially Disentangled Audio-Visual Representation）</news:title>
   <news:publication_date>2026-05-28T14:02:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695261</loc>
  <lastmod>2026-05-28T14:02:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つの質量を同時に扱う三ループ効果が示す精度改善（Two-mass three-loop effects in deep-inelastic scattering）</news:title>
   <news:publication_date>2026-05-28T14:02:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695259</loc>
  <lastmod>2026-05-28T14:02:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短い手術映像ショットのフェーズ認識（Surgical Phase Recognition of Short Video Shots Based on Temporal Modeling of Deep Features）</news:title>
   <news:publication_date>2026-05-28T14:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695257</loc>
  <lastmod>2026-05-28T14:01:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートシティ向け無線マルチセンサネットワークのプロトタイプと統計解析（Wireless Multi-Sensor Networks for Smart Cities: A Prototype System with Statistical Data Analysis）</news:title>
   <news:publication_date>2026-05-28T14:01:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-28T14:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>40,000コアでの対話型スーパーコンピューティングが切り開く機械学習の即時性（Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis）</news:title>
   <news:publication_date>2026-05-28T14:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695253</loc>
  <lastmod>2026-05-28T14:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェア分類における実験バイアス排除の方法（TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time）</news:title>
   <news:publication_date>2026-05-28T14:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695251</loc>
  <lastmod>2026-05-28T14:00:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合と連結：スキップ接続における比較（Competition vs. Concatenation in Skip Connections of Fully Convolutional Networks）</news:title>
   <news:publication_date>2026-05-28T14:00:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695249</loc>
  <lastmod>2026-05-28T13:09:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元類似度学習における次元の呪いの回避（Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds）</news:title>
   <news:publication_date>2026-05-28T13:09:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695247</loc>
  <lastmod>2026-05-28T13:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル非依存のサリエンシーによる乳房DCE-MRIの弱教師付き病変検出（MODEL AGNOSTIC SALIENCY FOR WEAKLY SUPERVISED LESION DETECTION FROM BREAST DCE-MRI）</news:title>
   <news:publication_date>2026-05-28T13:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695245</loc>
  <lastmod>2026-05-28T13:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの点群再構成を変える3D-LMNet（3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image）</news:title>
   <news:publication_date>2026-05-28T13:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695243</loc>
  <lastmod>2026-05-28T13:08:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理的敵対的例による物体検出器への攻撃（Physical Adversarial Examples for Object Detectors）</news:title>
   <news:publication_date>2026-05-28T13:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695241</loc>
  <lastmod>2026-05-28T13:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高強度・高コントラストフェムト秒レーザーの固体吸収挙動（Absorption of High Intensity, High Contrast Femtosecond Laser Pulses by a Solid）</news:title>
   <news:publication_date>2026-05-28T13:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695239</loc>
  <lastmod>2026-05-28T13:07:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAR画像変換のための弁証法的GAN（Dialectical GAN for SAR Image Translation: From Sentinel-1 to TerraSAR-X）</news:title>
   <news:publication_date>2026-05-28T13:07:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695237</loc>
  <lastmod>2026-05-28T13:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有表現に基づく文書クラスタリング（Semantic Document Clustering on Named Entity Features）</news:title>
   <news:publication_date>2026-05-28T13:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695235</loc>
  <lastmod>2026-05-28T12:16:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き文字認識を現場で使える形に変えた技術（An Efficient End-to-End Neural Model for Handwritten Text Recognition）</news:title>
   <news:publication_date>2026-05-28T12:16:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695233</loc>
  <lastmod>2026-05-28T12:15:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の事前学習済みCNNを用いた画像クラスタリングの改善（Improving Image Clustering With Multiple Pretrained CNN Feature Extractors）</news:title>
   <news:publication_date>2026-05-28T12:15:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695231</loc>
  <lastmod>2026-05-28T12:15:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数がもたらす依存構造の学習（Learning the effect of latent variables in Gaussian Graphical models with unobserved variables）</news:title>
   <news:publication_date>2026-05-28T12:15:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695229</loc>
  <lastmod>2026-05-28T12:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の行動を考慮した運動計画による近接協働の滑らかさ向上（Considering Human Behavior in Motion Planning for Smooth Human-Robot Collaboration in Close Proximity）</news:title>
   <news:publication_date>2026-05-28T12:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695227</loc>
  <lastmod>2026-05-28T12:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおける感情分析システム（Twitter Sentiment Analysis System）</news:title>
   <news:publication_date>2026-05-28T12:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695225</loc>
  <lastmod>2026-05-28T12:14:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトスキル表現の識別とマッチング（Learning Representations for Soft Skill Matching）</news:title>
   <news:publication_date>2026-05-28T12:14:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695223</loc>
  <lastmod>2026-05-28T12:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的な固体の表面張力がもたらす液滴のピニングとデピニング（Dynamic solid surface tension causes droplet pinning and depinning）</news:title>
   <news:publication_date>2026-05-28T12:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695221</loc>
  <lastmod>2026-05-28T11:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電圧オーバースケーリングに基づく軽量認証に対する機械学習攻撃と防御 (Machine Learning Attack and Defense on Voltage Over-scaling-based Lightweight Authentication)</news:title>
   <news:publication_date>2026-05-28T11:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695219</loc>
  <lastmod>2026-05-28T11:22:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍のセグメンテーションとトラクトグラフィー特徴量による生存予測（Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival Prediction）</news:title>
   <news:publication_date>2026-05-28T11:22:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695217</loc>
  <lastmod>2026-05-28T11:22:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問依存文ゲーティングによる問答精度向上（Question-Aware Sentence Gating Networks for Question and Answering）</news:title>
   <news:publication_date>2026-05-28T11:22:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695215</loc>
  <lastmod>2026-05-28T11:21:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字の二面性を捉える感情分析手法（Bi-sense Emoji Embedding for Twitter Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-28T11:21:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695213</loc>
  <lastmod>2026-05-28T11:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PhaseStainによるラベルフリー位相イメージのデジタル染色（PhaseStain: Digital staining of label-free quantitative phase microscopy images using deep learning）</news:title>
   <news:publication_date>2026-05-28T11:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695211</loc>
  <lastmod>2026-05-28T11:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標準模型を超える物理探索における効率的確率推論（Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model）</news:title>
   <news:publication_date>2026-05-28T11:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695209</loc>
  <lastmod>2026-05-28T11:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン活動認識のための深層転移学習（Deep Transfer Learning for Cross-domain Activity Recognition）</news:title>
   <news:publication_date>2026-05-28T11:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695207</loc>
  <lastmod>2026-05-28T10:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的コンテンツの自動除去（Automatic Semantic Content Removal by Learning to Neglect）</news:title>
   <news:publication_date>2026-05-28T10:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695205</loc>
  <lastmod>2026-05-28T10:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドなデータ駆動型深層学習で変わる流体–構造連成解析（DRAFT: A HYBRID DATA-DRIVEN DEEP LEARNING TECHNIQUE FOR FLUID-STRUCTURE INTERACTION）</news:title>
   <news:publication_date>2026-05-28T10:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695203</loc>
  <lastmod>2026-05-28T10:19:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Editable Generative Adversarial Networksによる顔画像の同時生成と編集（Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously）</news:title>
   <news:publication_date>2026-05-28T10:19:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695201</loc>
  <lastmod>2026-05-28T10:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的代替勾配を用いた一般化確率的Frank–Wolfe法（Generalized Stochastic Frank-Wolfe Algorithm with Stochastic “Substitute” Gradient for Structured Convex Optimization）</news:title>
   <news:publication_date>2026-05-28T10:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695199</loc>
  <lastmod>2026-05-28T10:18:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴を保持する画像ベースのバーチャルトライオンネットワーク（Toward Characteristic-Preserving Image-based Virtual Try-On Network）</news:title>
   <news:publication_date>2026-05-28T10:18:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695197</loc>
  <lastmod>2026-05-28T10:18:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブタスク依存を伴うゼロショット一般化のための階層強化学習（Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies）</news:title>
   <news:publication_date>2026-05-28T10:18:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695195</loc>
  <lastmod>2026-05-28T10:18:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全畳み込みニューラルネットワークによるエンドツーエンド音声強調（A FULLY CONVOLUTIONAL NEURAL NETWORK APPROACH TO END-TO-END SPEECH ENHANCEMENT）</news:title>
   <news:publication_date>2026-05-28T10:18:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695193</loc>
  <lastmod>2026-05-28T09:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星団パラメータ推定にCNNを用いる方法（Deriving star cluster parameters with convolutional neural networks. I. Age, mass, and size）</news:title>
   <news:publication_date>2026-05-28T09:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695191</loc>
  <lastmod>2026-05-28T09:26:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フーリエ変換走査型トンネル分光における辞書学習（Dictionary Learning in Fourier Transform Scanning Tunneling Spectroscopy）</news:title>
   <news:publication_date>2026-05-28T09:26:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695189</loc>
  <lastmod>2026-05-28T09:25:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像分割のためのCNNアーキテクチャ自動設計（Automatically Designing CNN Architectures for Medical Image Segmentation）</news:title>
   <news:publication_date>2026-05-28T09:25:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695187</loc>
  <lastmod>2026-05-28T09:25:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Expectation Propagationを用いた近似Collapsed Gibbsクラスタリング（Approximate Collapsed Gibbs Clustering with Expectation Propagation）</news:title>
   <news:publication_date>2026-05-28T09:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695185</loc>
  <lastmod>2026-05-28T09:25:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェアベースの高速時系列予測（Rapid Time Series Prediction with a Hardware-Based Reservoir Computer）</news:title>
   <news:publication_date>2026-05-28T09:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695183</loc>
  <lastmod>2026-05-28T09:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上での一般化された距離修復（Generalized Metric Repair on Graphs）</news:title>
   <news:publication_date>2026-05-28T09:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695181</loc>
  <lastmod>2026-05-28T09:24:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tsallis-INFによる確率的・敵対的バンディットの同時最適化（Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits）</news:title>
   <news:publication_date>2026-05-28T09:24:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695179</loc>
  <lastmod>2026-05-28T08:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データ下における教師なし距離学習（Unsupervised Metric Learning In Presence of Missing Data）</news:title>
   <news:publication_date>2026-05-28T08:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695177</loc>
  <lastmod>2026-05-28T08:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重確率的敵対的オートエンコーダの提案（Doubly Stochastic Adversarial Autoencoder）</news:title>
   <news:publication_date>2026-05-28T08:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695175</loc>
  <lastmod>2026-05-28T08:32:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常環境における適応変分パーティクルフィルタ（Adaptive Variational Particle Filtering in Non-stationary Environments）</news:title>
   <news:publication_date>2026-05-28T08:32:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695173</loc>
  <lastmod>2026-05-28T08:31:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像解析におけるカプセルネットワークの有効性（Capsule Networks against Medical Imaging Data Challenges）</news:title>
   <news:publication_date>2026-05-28T08:31:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695171</loc>
  <lastmod>2026-05-28T08:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェットを用いた横運動量依存分布の測定（Transverse momentum dependent distributions with jets）</news:title>
   <news:publication_date>2026-05-28T08:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695169</loc>
  <lastmod>2026-05-28T08:31:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冠動脈造影画像における狭窄の自動定量化（Automated Characterization of Stenosis in Invasive Coronary Angiography Images with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-28T08:31:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695167</loc>
  <lastmod>2026-05-28T08:31:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Compositional GANによる画像合成の新潮流（Compositional GAN: Learning Image-Conditional Binary Composition）</news:title>
   <news:publication_date>2026-05-28T08:31:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695165</loc>
  <lastmod>2026-05-28T07:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の表情解析における転移学習とモデルアンサンブル（Transfer Learning for Action Unit Recognition）</news:title>
   <news:publication_date>2026-05-28T07:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695163</loc>
  <lastmod>2026-05-28T07:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非滑らか・非凸最適化への幾何学的積分アプローチ（A geometric integration approach to nonsmooth, nonconvex optimisation）</news:title>
   <news:publication_date>2026-05-28T07:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695161</loc>
  <lastmod>2026-05-28T07:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リラックスドK平均法によるクラスタリングの部分復元境界（Partial recovery bounds for clustering with the relaxed K-means）</news:title>
   <news:publication_date>2026-05-28T07:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695159</loc>
  <lastmod>2026-05-28T07:39:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズフィルタリングによる最適化の統一（Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods）</news:title>
   <news:publication_date>2026-05-28T07:39:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695157</loc>
  <lastmod>2026-05-28T07:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダにおける補間の理解と改善（Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer）</news:title>
   <news:publication_date>2026-05-28T07:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695155</loc>
  <lastmod>2026-05-28T07:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>なじみの組み替え：再帰型ニューラルネットの合成的一般化検証（Rearranging the Familiar: Testing Compositional Generalization in Recurrent Networks）</news:title>
   <news:publication_date>2026-05-28T07:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695153</loc>
  <lastmod>2026-05-28T07:38:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意誘導カリキュラム学習による胸部X線の弱教師あり分類と局在化（Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs）</news:title>
   <news:publication_date>2026-05-28T07:38:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695151</loc>
  <lastmod>2026-05-28T06:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANでマルウェア作者を模倣して先回りする手法（Emulating malware authors for proactive protection using GANs over a distributed image visualization of dynamic file behavior）</news:title>
   <news:publication_date>2026-05-28T06:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695149</loc>
  <lastmod>2026-05-28T06:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化マップを用いた強化学習における知識蓄積と転送（Self-Organizing Maps as a Storage and Transfer Mechanism in Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-28T06:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695147</loc>
  <lastmod>2026-05-28T06:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膝の回復を支援する生体計測と機械学習（Bio-Measurements Estimation and Support in Knee Recovery through Machine Learning）</news:title>
   <news:publication_date>2026-05-28T06:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695145</loc>
  <lastmod>2026-05-28T06:45:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MR脳組織画像の示唆的アノテーション戦略（A Strategy of MR Brain Tissue Images&amp;#039; Suggestive Annotation Based on Modified U-Net）</news:title>
   <news:publication_date>2026-05-28T06:45:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695143</loc>
  <lastmod>2026-05-28T06:45:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータ工学教育における技術トレンドの追跡（Following Technology Trends in Computer Engineering Education）</news:title>
   <news:publication_date>2026-05-28T06:45:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695141</loc>
  <lastmod>2026-05-28T06:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純モデルを賢くする自信プロファイル転移法（Improving Simple Models with Confidence Profiles）</news:title>
   <news:publication_date>2026-05-28T06:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695139</loc>
  <lastmod>2026-05-28T06:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音適応型音声強調とドメイン逆学習（Noise Adaptive Speech Enhancement using Domain Adversarial Training）</news:title>
   <news:publication_date>2026-05-28T06:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695137</loc>
  <lastmod>2026-05-28T05:53:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学的ディスコードとエントロピー系ディスコードの関係を機械学習で探る（Machine learning study of the relationship between the geometric and entropy discord）</news:title>
   <news:publication_date>2026-05-28T05:53:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695135</loc>
  <lastmod>2026-05-28T05:53:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fuzzerと強化学習で変わるソフトウェア検査（FuzzerGym: A Competitive Framework for Fuzzing and Learning）</news:title>
   <news:publication_date>2026-05-28T05:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695133</loc>
  <lastmod>2026-05-28T05:52:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深いカーネル化オートエンコーダ（The Deep Kernelized Autoencoder）</news:title>
   <news:publication_date>2026-05-28T05:52:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695131</loc>
  <lastmod>2026-05-28T05:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所測定に基づくニューラルネットワークによる量子状態トモグラフィ（Local-measurement-based quantum state tomography via neural networks）</news:title>
   <news:publication_date>2026-05-28T05:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695129</loc>
  <lastmod>2026-05-28T05:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増強属性に基づく選択的ゼロショット分類（Selective Zero-Shot Classification with Augmented Attributes）</news:title>
   <news:publication_date>2026-05-28T05:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695127</loc>
  <lastmod>2026-05-28T05:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットワークによる重なり音検出の新展開（A Capsule based Approach for Polyphonic Sound Event Detection）</news:title>
   <news:publication_date>2026-05-28T05:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695125</loc>
  <lastmod>2026-05-28T05:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル単位で適応する畳み込み型ノイズ除去（Fully Convolutional Pixel Adaptive Image Denoiser）</news:title>
   <news:publication_date>2026-05-28T05:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695123</loc>
  <lastmod>2026-05-28T05:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的文脈のモデリングが物体検出データ拡張の鍵である（Modeling Visual Context is Key to Augmenting Object Detection Datasets）</news:title>
   <news:publication_date>2026-05-28T05:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695121</loc>
  <lastmod>2026-05-28T04:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動学的ネットワークによるリアルタイム手持ち音速イメージング（Image Reconstruction via Variational Network for Real-Time Hand-Held Sound-Speed Imaging）</news:title>
   <news:publication_date>2026-05-28T04:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695119</loc>
  <lastmod>2026-05-28T04:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>持続可能な研究ソフトウェアの現状：WSSSPE5.1の報告（The State of Sustainable Research Software: Results from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1)）</news:title>
   <news:publication_date>2026-05-28T04:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695117</loc>
  <lastmod>2026-05-28T04:58:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EchoFusionによる4Dフリーハンド超音波イメージングの追跡と再構成（EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers）</news:title>
   <news:publication_date>2026-05-28T04:58:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695115</loc>
  <lastmod>2026-05-28T04:58:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープ畳み込みニューラルネットワークのハイパーパラメータ最適化の高速化（Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-28T04:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695113</loc>
  <lastmod>2026-05-28T04:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアとスマート機器でメンタルヘルスを評価できるか（Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation）</news:title>
   <news:publication_date>2026-05-28T04:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695111</loc>
  <lastmod>2026-05-28T04:57:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像セグメンテーションにおけるテスト時拡張を用いたアレアトリック不確実性推定（Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks）</news:title>
   <news:publication_date>2026-05-28T04:57:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695109</loc>
  <lastmod>2026-05-28T04:06:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MR-CT 変形イメージ登録のための生成的敵対ネットワーク（Generative Adversarial Networks for MR-CT Deformable Image Registration）</news:title>
   <news:publication_date>2026-05-28T04:06:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695107</loc>
  <lastmod>2026-05-28T04:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワークフロー実行の履歴パターンを索引化する方法（Indexing Execution Patterns in Workflow Provenance Graphs through Generalized Trie Structures）</news:title>
   <news:publication_date>2026-05-28T04:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695105</loc>
  <lastmod>2026-05-28T04:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子層積層で実現する干渉不要の偏光分離（Interferenceless Polarization Splitting through Nanoscale van der Waals Heterostructures）</news:title>
   <news:publication_date>2026-05-28T04:05:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695103</loc>
  <lastmod>2026-05-28T04:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sequence to Logic with Copy and Cache（Sequence to Logic with Copy and Cache）</news:title>
   <news:publication_date>2026-05-28T04:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695101</loc>
  <lastmod>2026-05-28T04:04:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学リモートセンシング画像における物体検出のための深層適応提案ネットワーク（Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images）</news:title>
   <news:publication_date>2026-05-28T04:04:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695099</loc>
  <lastmod>2026-05-28T04:04:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報伝達率で性能と解釈性を制御する変分オートエンコーダ（Bounded Information Rate Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-28T04:04:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695097</loc>
  <lastmod>2026-05-28T04:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細部認識を強化するゲーテッド注意機構（Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery）</news:title>
   <news:publication_date>2026-05-28T04:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695095</loc>
  <lastmod>2026-05-28T03:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学術推薦のための公開オンライン評価基盤：Mr. DLibのリビングラボ（Online Evaluations for Everyone: Mr. DLib’s Living Lab for Scholarly Recommendations）</news:title>
   <news:publication_date>2026-05-28T03:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695093</loc>
  <lastmod>2026-05-28T03:10:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オペレータ・イン・ザ・ループによる逐次的マルチカメラ特徴融合で変わる人物再識別（Operator-in-the-Loop Deep Sequential Multi-camera Feature Fusion for Person Re-identification）</news:title>
   <news:publication_date>2026-05-28T03:10:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695091</loc>
  <lastmod>2026-05-28T03:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインラベル集約の変革：漸次的変分ベイズ法によるBiLA（Online Label Aggregation: A Variational Bayesian Approach）</news:title>
   <news:publication_date>2026-05-28T03:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695089</loc>
  <lastmod>2026-05-28T03:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセルラベリングから物体局所化とシーン分類へ（In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization）</news:title>
   <news:publication_date>2026-05-28T03:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695087</loc>
  <lastmod>2026-05-28T03:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水処理制御システムの異常検知を自動最適化する手法（Anomaly Detection for Water Treatment System based on Neural Network with Automatic Architecture Optimization）</news:title>
   <news:publication_date>2026-05-28T03:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695085</loc>
  <lastmod>2026-05-28T03:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列波形生成とエンドツーエンド音声合成の革新（ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech）</news:title>
   <news:publication_date>2026-05-28T03:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695083</loc>
  <lastmod>2026-05-28T02:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニホールド埋め込み分布整合による視覚ドメイン適応（Visual Domain Adaptation with Manifold Embedded Distribution Alignment）</news:title>
   <news:publication_date>2026-05-28T02:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695081</loc>
  <lastmod>2026-05-28T02:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いた特徴のない信号生成（Machine Learning Based Featureless Signalling）</news:title>
   <news:publication_date>2026-05-28T02:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695079</loc>
  <lastmod>2026-05-28T02:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学力リスク予測における機械学習の限界（MACHINE LEARNING CLASSIFIERS DO NOT IMPROVE THE PREDICTION OF ACADEMIC RISK: EVIDENCE FROM AUSTRALIA）</news:title>
   <news:publication_date>2026-05-28T02:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695077</loc>
  <lastmod>2026-05-28T02:16:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話行為に基づく説明可能で制御可能なオープンドメイン対話生成（Towards Explainable and Controllable Open Domain Dialogue Generation with Dialogue Acts）</news:title>
   <news:publication_date>2026-05-28T02:16:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695075</loc>
  <lastmod>2026-05-28T02:16:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像の多ラベル・微細分類問題の解法（Chest X-rays Classification: a Multi-Label and Fine-Grained Problem）</news:title>
   <news:publication_date>2026-05-28T02:16:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695073</loc>
  <lastmod>2026-05-28T02:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢バイアスを取り除く表現学習による認知症評価の新基準（Deconfounding age effects with fair representation learning when assessing dementia）</news:title>
   <news:publication_date>2026-05-28T02:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695071</loc>
  <lastmod>2026-05-28T01:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みの多ラベル評価と固有名詞の精緻な型付け（Evaluating Word Embeddings in Multi-label Classification Using Fine-grained Name Typing）</news:title>
   <news:publication_date>2026-05-28T01:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695069</loc>
  <lastmod>2026-05-28T01:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット適応によるマルチメディア意味索引の革新（Few-Shot Adaptation for Multimedia Semantic Indexing）</news:title>
   <news:publication_date>2026-05-28T01:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695067</loc>
  <lastmod>2026-05-28T01:16:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Projection Pursuit Forestによる分類木の革新（A Projection Pursuit Forest Algorithm for Supervised Classification）</news:title>
   <news:publication_date>2026-05-28T01:16:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695065</loc>
  <lastmod>2026-05-28T01:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に大きなコーパスでの効率的学習（Efficient Training on Very Large Corpora via Gramian Estimation）</news:title>
   <news:publication_date>2026-05-28T01:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695063</loc>
  <lastmod>2026-05-28T01:15:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルプラットフォーム向けソフトウェア開発の自動化（Automating Software Development for Mobile Computing Platforms）</news:title>
   <news:publication_date>2026-05-28T01:15:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695061</loc>
  <lastmod>2026-05-28T01:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学生質問の非効果的判定を自動化する研究（Automatic Identification of Ineffective Online Student Questions in Computing Education）</news:title>
   <news:publication_date>2026-05-28T01:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695059</loc>
  <lastmod>2026-05-28T01:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典新星における塵形成の分光学的診断（Spectroscopic diagnostics of dust formation and evolution in classical nova ejecta）</news:title>
   <news:publication_date>2026-05-28T01:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695057</loc>
  <lastmod>2026-05-28T00:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散した電波パルスの単一パルス探索に機械学習を組み合わせる新手法（A novel single-pulse search approach to detection of dispersed radio pulses using clustering and supervised machine learning）</news:title>
   <news:publication_date>2026-05-28T00:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695055</loc>
  <lastmod>2026-05-28T00:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による多モードファイバ内部の高変動性とランダム性の学習（Deep learning the high variability and randomness inside multimode fibres）</news:title>
   <news:publication_date>2026-05-28T00:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695053</loc>
  <lastmod>2026-05-28T00:22:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク二値行列近似の近似スキーム（Approximation Schemes for Low-Rank Binary Matrix Approximation Problems）</news:title>
   <news:publication_date>2026-05-28T00:22:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695051</loc>
  <lastmod>2026-05-28T00:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPIESデータベースの掘り下げ（Mining the GPIES database）</news:title>
   <news:publication_date>2026-05-28T00:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695049</loc>
  <lastmod>2026-05-28T00:21:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gemini Planet Imagerの5年間の総括と展望（The Gemini Planet Imager: Looking back over five years and forward to the future）</news:title>
   <news:publication_date>2026-05-28T00:21:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695047</loc>
  <lastmod>2026-05-28T00:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>街並みを読み解いて不動産価格を推定する（Take a Look Around: Using Street View and Satellite Images to Estimate House Prices）</news:title>
   <news:publication_date>2026-05-28T00:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695045</loc>
  <lastmod>2026-05-28T00:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像強調による病変セグメンテーション改善（CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement）</news:title>
   <news:publication_date>2026-05-28T00:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695043</loc>
  <lastmod>2026-05-27T23:29:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現の効率は行動効率に勝る：人間のプログラム誘導に関する研究 (Representational efficiency outweighs action efficiency in human program induction)</news:title>
   <news:publication_date>2026-05-27T23:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695041</loc>
  <lastmod>2026-05-27T23:29:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Newton-ADMM: 分散GPU加速型分類最適化器の要点解説 (Newton-ADMM: A Distributed GPU-Accelerated Optimizer for Multiclass Classification Problems)</news:title>
   <news:publication_date>2026-05-27T23:29:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695039</loc>
  <lastmod>2026-05-27T23:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線治療計画における脳腫瘍と危険臓器のモダリティ適応セグメンテーション（A Modality-Adaptive Method for Segmenting Brain Tumors and Organs-at-Risk in Radiation Therapy Planning）</news:title>
   <news:publication_date>2026-05-27T23:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695037</loc>
  <lastmod>2026-05-27T23:28:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AGN駆動分子流出が示すクエンチングの主役（molecular and ionized components of the AGN-driven outflow in zC400528）</news:title>
   <news:publication_date>2026-05-27T23:28:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695035</loc>
  <lastmod>2026-05-27T23:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力卸売市場価格予測の全体論的アプローチ（A Holistic Approach to Forecasting Wholesale Energy Market Prices）</news:title>
   <news:publication_date>2026-05-27T23:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695033</loc>
  <lastmod>2026-05-27T23:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療用植物のFTIRデータにおける離散ウェーブレット変換とウェーブレットテンソルトレイン分解の比較研究（Comparative study of Discrete Wavelet Transforms and Wavelet Tensor Train decomposition to feature extraction of FTIR data of medicinal plants）</news:title>
   <news:publication_date>2026-05-27T23:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695031</loc>
  <lastmod>2026-05-27T23:27:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチタスク学習とCTC（Hierarchical Multitask Learning with CTC）</news:title>
   <news:publication_date>2026-05-27T23:27:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695029</loc>
  <lastmod>2026-05-27T22:36:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CFPB消費者苦情のトピックモデリングにおけるLDAの適用（Latent Dirichlet Allocation for Topic Modeling of the CFPB Consumer Complaints）</news:title>
   <news:publication_date>2026-05-27T22:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695027</loc>
  <lastmod>2026-05-27T22:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭で学ぶロボット学習：汎化力向上とデータセットバイアスの低減（Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias）</news:title>
   <news:publication_date>2026-05-27T22:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695025</loc>
  <lastmod>2026-05-27T22:35:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNへの位置情報付与が変える画素理解の精度（Location Augmentation for CNN）</news:title>
   <news:publication_date>2026-05-27T22:35:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695023</loc>
  <lastmod>2026-05-27T22:35:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層横断最適化による高速加算器設計（Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach）</news:title>
   <news:publication_date>2026-05-27T22:35:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695021</loc>
  <lastmod>2026-05-27T22:35:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立整数確率変数の和を学ぶ（Learning Sums of Independent Random Variables with Sparse Collective Support）</news:title>
   <news:publication_date>2026-05-27T22:35:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695019</loc>
  <lastmod>2026-05-27T22:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる多電子シュレーディンガー方程式の解法 (Solving Many-Electron Schrödinger Equation Using Deep Neural Networks)</news:title>
   <news:publication_date>2026-05-27T22:34:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695017</loc>
  <lastmod>2026-05-27T22:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>骨格運動を色情報に変換する新表現（Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks）</news:title>
   <news:publication_date>2026-05-27T22:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695015</loc>
  <lastmod>2026-05-27T21:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>投資対効果で選ぶモデル評価指標（Is it worth it? Budget-related evaluation metrics for model selection）</news:title>
   <news:publication_date>2026-05-27T21:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695013</loc>
  <lastmod>2026-05-27T21:43:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変のセグメンテーションと分類（Skin Lesion Segmentation and Classification for ISIC 2018 Using Traditional Classifiers with Hand-Crafted Features）</news:title>
   <news:publication_date>2026-05-27T21:43:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695011</loc>
  <lastmod>2026-05-27T21:42:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Scalable PANFISに基づく大規模データストリーム分析の進化（Evolving Large-Scale Data Stream Analytics based on Scalable PANFIS）</news:title>
   <news:publication_date>2026-05-27T21:42:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695009</loc>
  <lastmod>2026-05-27T21:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点ごとのROC最適化のための確率的類似度学習理論（A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization）</news:title>
   <news:publication_date>2026-05-27T21:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695007</loc>
  <lastmod>2026-05-27T21:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差検証に基づくGMMによるモデル選択（Cross Validation Based Model Selection via Generalized Method of Moments）</news:title>
   <news:publication_date>2026-05-27T21:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695005</loc>
  <lastmod>2026-05-27T21:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーションのための能動学習：情報量最適化による最大エントロピー戦略（Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy）</news:title>
   <news:publication_date>2026-05-27T21:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695003</loc>
  <lastmod>2026-05-27T21:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成レビューで説明可能なレコメンダを強化する手法（Improving Explainable Recommendations with Synthetic Reviews）</news:title>
   <news:publication_date>2026-05-27T21:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695001</loc>
  <lastmod>2026-05-27T20:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像復元のためのハイブリッドスパース事前学習（Learning Hybrid Sparsity Prior for Image Restoration: Where Deep Learning Meets Sparse Coding）</news:title>
   <news:publication_date>2026-05-27T20:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694999</loc>
  <lastmod>2026-05-27T20:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肝臓DCE-MRIにおける動きアーチファクト低減のための畳み込みニューラルネットワーク（Method for motion artifact reduction using a convolutional neural network for dynamic contrast enhanced MRI of the liver）</news:title>
   <news:publication_date>2026-05-27T20:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694997</loc>
  <lastmod>2026-05-27T20:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Backplayによる強化学習の効率化（BACKPLAY: &amp;#039;MAN MUSS IMMER UMKEHREN&amp;#039;）</news:title>
   <news:publication_date>2026-05-27T20:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694995</loc>
  <lastmod>2026-05-27T20:39:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なニューラルアーキテクチャとハイパーパラメータの同時探索（Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search）</news:title>
   <news:publication_date>2026-05-27T20:39:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694993</loc>
  <lastmod>2026-05-27T20:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習支援型QKDの実地検証とSDN統合（Field-Trial of Machine Learning-Assisted Quantum Key Distribution (QKD) Networking with SDN）</news:title>
   <news:publication_date>2026-05-27T20:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694991</loc>
  <lastmod>2026-05-27T20:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シェイプリー濃縮核での宇宙の舞踏—BCGと尾状電波銀河の研究（Cosmic dance in the Shapley Concentration Core – I. A study of the radio emission of the BCGs and tailed radio galaxies）</news:title>
   <news:publication_date>2026-05-27T20:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694989</loc>
  <lastmod>2026-05-27T20:38:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RARD II：9400万件の関連論文推薦データセット（RARD II: The 94 Million Related-Article Recommendation Dataset）</news:title>
   <news:publication_date>2026-05-27T20:38:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694987</loc>
  <lastmod>2026-05-27T19:47:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な近似地震波シミュレーション（Fast approximate simulation of seismic waves with deep learning）</news:title>
   <news:publication_date>2026-05-27T19:47:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694985</loc>
  <lastmod>2026-05-27T19:46:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートン星の地殻における爆発後熱緩和の理解（Afterburst thermal relaxation in neutron star crusts）</news:title>
   <news:publication_date>2026-05-27T19:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694983</loc>
  <lastmod>2026-05-27T19:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低遅延用途向けに知覚的可解度を直接最適化する音声分離（DEEP NEURAL NETWORK BASED SPEECH SEPARATION OPTIMIZING AN OBJECTIVE ESTIMATOR OF INTELLIGIBILITY FOR LOW LATENCY APPLICATIONS）</news:title>
   <news:publication_date>2026-05-27T19:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694981</loc>
  <lastmod>2026-05-27T19:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセット間転移のためのメトリック埋め込みオートエンコーダ（Metric Embedding Autoencoders for Unsupervised Cross-Dataset Transfer Learning）</news:title>
   <news:publication_date>2026-05-27T19:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694979</loc>
  <lastmod>2026-05-27T19:45:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースに基づくトレーディング戦略（News-based trading strategies）</news:title>
   <news:publication_date>2026-05-27T19:45:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694977</loc>
  <lastmod>2026-05-27T19:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークを用いた学習可能な交差を持つ遺伝的アルゴリズム（Genetic algorithms with DNN-based trainable crossover as an example of partial specialization of general search）</news:title>
   <news:publication_date>2026-05-27T19:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694975</loc>
  <lastmod>2026-05-27T19:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な解剖学的特徴の学習と心臓リモデリングへの応用（Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling）</news:title>
   <news:publication_date>2026-05-27T19:45:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694973</loc>
  <lastmod>2026-05-27T18:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河とクエーサーの未来像—マルチメッセンジャー天文学がもたらす30年の変化（A multimessenger view of galaxies and quasars from now to mid-century）</news:title>
   <news:publication_date>2026-05-27T18:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694971</loc>
  <lastmod>2026-05-27T18:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像の解像度向上を目指す3D畳み込みニューラルネットワーク（Computed Tomography Image Enhancement using 3D Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-27T18:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694969</loc>
  <lastmod>2026-05-27T18:53:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異値分解を用いた自己教師ありナレッジ蒸留（Self-supervised Knowledge Distillation Using Singular Value Decomposition）</news:title>
   <news:publication_date>2026-05-27T18:53:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694967</loc>
  <lastmod>2026-05-27T18:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lp輸送コストに関する中心極限定理と機械学習における公平性評価への応用 (A Central Limit Theorem for Lp transportation cost with applications to Fairness Assessment in Machine Learning)</news:title>
   <news:publication_date>2026-05-27T18:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694965</loc>
  <lastmod>2026-05-27T18:51:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしオンラインマルチタスクによる行動文埋め込みの学習（Unsupervised Online Multitask Learning of Behavioral Sentence Embeddings）</news:title>
   <news:publication_date>2026-05-27T18:51:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694963</loc>
  <lastmod>2026-05-27T18:51:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Content-User Embedding Modelによる音楽推薦の実際（Deep Content-User Embedding Model for Music Recommendation）</news:title>
   <news:publication_date>2026-05-27T18:51:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694961</loc>
  <lastmod>2026-05-27T18:51:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DroNet：リアルタイムUAV用途のための効率的CNN検出器（DroNet: Efficient Convolutional Neural Network Detector for Real-Time UAV Applications）</news:title>
   <news:publication_date>2026-05-27T18:51:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694959</loc>
  <lastmod>2026-05-27T17:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的アフォーダンスと機能理解の総説（Visual Affordance and Function Understanding: A Survey）</news:title>
   <news:publication_date>2026-05-27T17:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694957</loc>
  <lastmod>2026-05-27T17:58:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RMSPropとADAMの収束保証と実証的比較（Convergence guarantees for RMSProp and ADAM in non-convex optimization and an empirical comparison to Nesterov acceleration）</news:title>
   <news:publication_date>2026-05-27T17:58:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694955</loc>
  <lastmod>2026-05-27T17:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UNet++による医療画像セグメンテーション（UNet++: A Nested U-Net Architecture for Medical Image Segmentation）</news:title>
   <news:publication_date>2026-05-27T17:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694953</loc>
  <lastmod>2026-05-27T17:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>具現化されたナビゲーションエージェントの評価について（On Evaluation of Embodied Navigation Agents）</news:title>
   <news:publication_date>2026-05-27T17:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694951</loc>
  <lastmod>2026-05-27T17:56:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SySeVRフレームワークによる脆弱性検出（SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities）</news:title>
   <news:publication_date>2026-05-27T17:56:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694949</loc>
  <lastmod>2026-05-27T17:55:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンの継続認証におけるアプリ利用パターンの活用（Continuous Authentication of Smartphones Based on Application Usage）</news:title>
   <news:publication_date>2026-05-27T17:55:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694947</loc>
  <lastmod>2026-05-27T17:55:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的価値関数ネットワーク（General Value Function Networks）</news:title>
   <news:publication_date>2026-05-27T17:55:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694945</loc>
  <lastmod>2026-05-27T17:04:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LAA-LTEベースHetNetsの学習による共存機構（A Learning-Based Coexistence Mechanism for LAA-LTE Based HetNets）</news:title>
   <news:publication_date>2026-05-27T17:04:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694943</loc>
  <lastmod>2026-05-27T17:04:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元ディラック半金属におけるランドー準位からエフィモフ様結合状態への転移（Landau Level to Efimov-like Bound State Crossover in Two-dimensional Dirac Semimetals）</news:title>
   <news:publication_date>2026-05-27T17:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694941</loc>
  <lastmod>2026-05-27T17:03:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多形状挿入のための実験的力・トルクセンサデータセット（Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion）</news:title>
   <news:publication_date>2026-05-27T17:03:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694939</loc>
  <lastmod>2026-05-27T17:02:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前立腺MR体積セグメンテーションのための3D Global Convolutional Adversarial Network（3D Global Convolutional Adversarial Network for Prostate MR Volume Segmentation）</news:title>
   <news:publication_date>2026-05-27T17:02:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694937</loc>
  <lastmod>2026-05-27T17:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の解釈可能性はツールではなく科学である（Machine Learning Interpretability: A Science rather than a tool）</news:title>
   <news:publication_date>2026-05-27T17:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694935</loc>
  <lastmod>2026-05-27T17:02:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例研究におけるゲーム規則の動機づけ（Motivating the Rules of the Game for Adversarial Example Research）</news:title>
   <news:publication_date>2026-05-27T17:02:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694933</loc>
  <lastmod>2026-05-27T17:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声合成における順方向注意機構（Forward Attention in Sequence-to-Sequence Acoustic Modeling for Speech Synthesis）</news:title>
   <news:publication_date>2026-05-27T17:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694923</loc>
  <lastmod>2026-05-27T16:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化関数の量子化で攻撃に強くする（Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions）</news:title>
   <news:publication_date>2026-05-27T16:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694921</loc>
  <lastmod>2026-05-27T16:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングと予測の相互作用が生む誤差 — Out-of-Cluster損失推定の落とし穴（On the Interaction Effects Between Prediction and Clustering）</news:title>
   <news:publication_date>2026-05-27T16:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694919</loc>
  <lastmod>2026-05-27T16:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのあるレベルセット推定におけるガウス過程メタモデルと逐次設計の評価（Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation）</news:title>
   <news:publication_date>2026-05-27T16:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694917</loc>
  <lastmod>2026-05-27T16:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的ニューラルツリー（Adaptive Neural Trees）</news:title>
   <news:publication_date>2026-05-27T16:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694915</loc>
  <lastmod>2026-05-27T16:09:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SVMによるROC曲線と信頼帯の推定（Receiver Operating Characteristic Curves and Confidence Bands for Support Vector Machines）</news:title>
   <news:publication_date>2026-05-27T16:09:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694913</loc>
  <lastmod>2026-05-27T16:09:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下ナビゲーションのためのアルゴリズム計画と深層学習の統合（Integrating Algorithmic Planning and Deep Learning for Partially Observable Navigation）</news:title>
   <news:publication_date>2026-05-27T16:09:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694911</loc>
  <lastmod>2026-05-27T16:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習のための変調モジュールと画像検索への応用（A Modulation Module for Multi-task Learning with Applications in Image Retrieval）</news:title>
   <news:publication_date>2026-05-27T16:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694909</loc>
  <lastmod>2026-05-27T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不一致と異質性下における加法インデックスモデルのテンソル法 (Tensor Methods for Additive Index Models under Discordance and Heterogeneity)</news:title>
   <news:publication_date>2026-05-27T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694907</loc>
  <lastmod>2026-05-27T15:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ソースの機密データで効率的に学習する仕組み（Efficient Deep Learning on Multi-Source Private Data）</news:title>
   <news:publication_date>2026-05-27T15:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694905</loc>
  <lastmod>2026-05-27T15:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スーパーモジュラな局所感度ハッシュ（Supermodular Locality Sensitive Hashes）</news:title>
   <news:publication_date>2026-05-27T15:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694903</loc>
  <lastmod>2026-05-27T15:16:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェアのトレース情報を自動で保守する考え方（Automatic Traceability Maintenance via Machine Learning Classification）</news:title>
   <news:publication_date>2026-05-27T15:16:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694901</loc>
  <lastmod>2026-05-27T15:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画向け高速セマンティックセグメンテーションのための補正融合ネットワーク（Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video）</news:title>
   <news:publication_date>2026-05-27T15:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694899</loc>
  <lastmod>2026-05-27T15:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形態タグの同時曖昧さ解消で向上する固有表現認識（Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags）</news:title>
   <news:publication_date>2026-05-27T15:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694897</loc>
  <lastmod>2026-05-27T15:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ条件付き動画要約の新しい枠組み（Query-Conditioned Three-Player Adversarial Network for Video Summarization）</news:title>
   <news:publication_date>2026-05-27T15:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694895</loc>
  <lastmod>2026-05-27T14:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mixed-Stationary Gaussian Processによる空間データの柔軟な非定常性モデリング（Mixed-Stationary Gaussian Process for Flexible Non-Stationary Modeling of Spatial Outcomes）</news:title>
   <news:publication_date>2026-05-27T14:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694893</loc>
  <lastmod>2026-05-27T14:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>旅客記録（PNR）の合成生成に挑むGAN手法（Airline Passenger Name Record Generation using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-27T14:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694891</loc>
  <lastmod>2026-05-27T14:23:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無ラベル画像分類とセグメンテーションを変えた手法（Invariant Information Clustering for Unsupervised Image Classification and Segmentation）</news:title>
   <news:publication_date>2026-05-27T14:23:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694889</loc>
  <lastmod>2026-05-27T14:22:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床テキスト分類におけるルールベース特徴と知識導入CNN（Clinical Text Classification with Rule-based Features and Knowledge-guided Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-27T14:22:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694887</loc>
  <lastmod>2026-05-27T14:22:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間補間に対する敵対的訓練による凸性の促進（Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourages convex latent distributions）</news:title>
   <news:publication_date>2026-05-27T14:22:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694885</loc>
  <lastmod>2026-05-27T14:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Autoencodersと異種事前分布による推薦改善（Item Recommendation with Variational Autoencoders and Heterogeneous Priors）</news:title>
   <news:publication_date>2026-05-27T14:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694883</loc>
  <lastmod>2026-05-27T14:21:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューリスティクスを越えて――データから学ぶ可視化デザイン（Beyond Heuristics: Learning Visualization Design）</news:title>
   <news:publication_date>2026-05-27T14:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694881</loc>
  <lastmod>2026-05-27T13:30:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポータブルな自然言語処理を用いたフェノタイピングシステムの開発（Developing a Portable Natural Language Processing Based Phenotyping System）</news:title>
   <news:publication_date>2026-05-27T13:30:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694879</loc>
  <lastmod>2026-05-27T13:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外積多様体によるフィードフォワードニューラルネットの表現力（Expressive power of outer product manifolds on feed-forward neural networks）</news:title>
   <news:publication_date>2026-05-27T13:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694877</loc>
  <lastmod>2026-05-27T13:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル平均化による高速かつ低通信の並列再起動SGD（Parallel Restarted SGD with Faster Convergence and Less Communication）</news:title>
   <news:publication_date>2026-05-27T13:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694875</loc>
  <lastmod>2026-05-27T13:28:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ロボットシステム向け深層強化学習（Deep Reinforcement Learning for Swarm Systems）</news:title>
   <news:publication_date>2026-05-27T13:28:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694873</loc>
  <lastmod>2026-05-27T13:28:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Libor Market Model向けの深層学習ベースBSDEソルバーとその実務的意義（Deep Learning-Based BSDE Solver for Libor Market Model with Application to Bermudan Swaption Pricing and Hedging）</news:title>
   <news:publication_date>2026-05-27T13:28:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694871</loc>
  <lastmod>2026-05-27T13:28:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海馬ROIにおけるsMRIとMD-DTIの融合を用いた3D InceptionベースCNNによるアルツハイマー病診断（3D Inception-based CNN with sMRI and MD-DTI data fusion for Alzheimer’s Disease diagnostics）</news:title>
   <news:publication_date>2026-05-27T13:28:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694869</loc>
  <lastmod>2026-05-27T13:27:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音不変表現による堅牢な音声認識 (Learning Noise-Invariant Representations for Robust Speech Recognition)</news:title>
   <news:publication_date>2026-05-27T13:27:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694867</loc>
  <lastmod>2026-05-27T12:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核子のパートン分布とハドロン量子揺らぎ（Nucleon parton distributions from hadronic quantum fluctuations）</news:title>
   <news:publication_date>2026-05-27T12:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694865</loc>
  <lastmod>2026-05-27T12:35:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照画像を用いた深層色付け（Deep Exemplar-based Colorization）</news:title>
   <news:publication_date>2026-05-27T12:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694863</loc>
  <lastmod>2026-05-27T12:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習からの示示における解釈可能な潜在空間（Interpretable Latent Spaces for Learning from Demonstration）</news:title>
   <news:publication_date>2026-05-27T12:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694861</loc>
  <lastmod>2026-05-27T12:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNエンコーダ・デコーダを異常検知に使うときの要点（Comparison of RNN Encoder-Decoder Models for Anomaly Detection）</news:title>
   <news:publication_date>2026-05-27T12:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694859</loc>
  <lastmod>2026-05-27T12:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Jensen：生産環境向け凸最適化と機械学習の拡れたツールキット（Jensen: An Easily-Extensible Toolkit for Convex Optimization and Machine Learning）</news:title>
   <news:publication_date>2026-05-27T12:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694857</loc>
  <lastmod>2026-05-27T12:32:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列と内容を同時に組み込むネットワーク埋め込み手法（Using link and content over time for embedding generation in Dynamic Attributed Networks）</news:title>
   <news:publication_date>2026-05-27T12:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694855</loc>
  <lastmod>2026-05-27T12:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Random Forest近接距離による特徴寄与の解明 (Explicating feature contribution using Random Forest proximity distances)</news:title>
   <news:publication_date>2026-05-27T12:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694853</loc>
  <lastmod>2026-05-27T11:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習後の「仕上げ」手法：Icing on the Cake（Icing on the Cake: An Easy and Quick Post-Learning Method You Can Try After Deep Learning）</news:title>
   <news:publication_date>2026-05-27T11:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694851</loc>
  <lastmod>2026-05-27T11:40:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模3D形状コレクションのセグメンテーションのための深層学習駆動型アクティブフレームワーク（A Deep Learning Driven Active Framework for Segmentation of Large 3D Shape Collections）</news:title>
   <news:publication_date>2026-05-27T11:40:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694849</loc>
  <lastmod>2026-05-27T11:40:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを前提に学習するRNNの実用性（Training Recurrent Neural Networks against Noisy Computations during Inference）</news:title>
   <news:publication_date>2026-05-27T11:40:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694847</loc>
  <lastmod>2026-05-27T11:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシング画像に深層学習を適用するためのフレームワーク（A framework for remote sensing images processing using deep learning techniques）</news:title>
   <news:publication_date>2026-05-27T11:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694845</loc>
  <lastmod>2026-05-27T11:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ制約下・ストリーミングPCAの加速スキーム（An Acceleration Scheme for Memory Limited, Streaming PCA）</news:title>
   <news:publication_date>2026-05-27T11:38:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694843</loc>
  <lastmod>2026-05-27T11:38:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cavity Filling: マルチクラス不均衡データに対する擬似特徴生成法（Cavity Filling: Pseudo-Feature Generation for Multi-Class Imbalanced Data Problems in Deep Learning）</news:title>
   <news:publication_date>2026-05-27T11:38:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694841</loc>
  <lastmod>2026-05-27T11:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PIMMS: 順序不変の多モーダルセグメンテーション（Permutation Invariant Multi-Modal Segmentation）</news:title>
   <news:publication_date>2026-05-27T11:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694839</loc>
  <lastmod>2026-05-27T10:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的品揃え最適化とログイット選択確率（Continuous Assortment Optimization with Logit Choice Probabilities under Incomplete Information）</news:title>
   <news:publication_date>2026-05-27T10:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694837</loc>
  <lastmod>2026-05-27T10:46:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電カオンの半包接近散乱における多産率の比較（Charged Kaon multiplicities of Semi-inclusive DIS off the deuteron target）</news:title>
   <news:publication_date>2026-05-27T10:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694835</loc>
  <lastmod>2026-05-27T10:45:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボトルネック・アテンション・モジュールによる特徴改良の効率化（Bottleneck Attention Module）</news:title>
   <news:publication_date>2026-05-27T10:45:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694833</loc>
  <lastmod>2026-05-27T10:45:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線治療の自動化を変えたGANの適用（Automated Radiation Therapy using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-27T10:45:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694831</loc>
  <lastmod>2026-05-27T10:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテクスチュアル・メモリ・ツリー（Contextual Memory Tree）</news:title>
   <news:publication_date>2026-05-27T10:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694829</loc>
  <lastmod>2026-05-27T10:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的サンプリングとグラフィカルモデル（Dynamic Sampling from Graphical Models）</news:title>
   <news:publication_date>2026-05-27T10:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694827</loc>
  <lastmod>2026-05-27T10:44:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>著者スタイルを模した多言語詩生成の手法（GUESS WHO? MULTILINGUAL APPROACH FOR THE AUTOMATED GENERATION OF AUTHOR-STYLIZED POETRY）</news:title>
   <news:publication_date>2026-05-27T10:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694825</loc>
  <lastmod>2026-05-27T09:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層完全畳み込みネットワークによる皮膚病変セグメンテーション（Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks）</news:title>
   <news:publication_date>2026-05-27T09:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694823</loc>
  <lastmod>2026-05-27T09:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2ビット量子化ニューラルネットワークの精度ギャップを埋める手法（Bridging the Accuracy Gap for 2-bit Quantized Neural Networks）</news:title>
   <news:publication_date>2026-05-27T09:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694821</loc>
  <lastmod>2026-05-27T09:51:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源音響イベント検出におけるデータ効率的弱教師あり学習（Data-efficient Weakly Supervised Learning for Low-Resource Audio Event Detection Using Deep Learning）</news:title>
   <news:publication_date>2026-05-27T09:51:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694819</loc>
  <lastmod>2026-05-27T09:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変分類におけるDense CNNアプローチ（A Dense CNN approach for skin lesion classification）</news:title>
   <news:publication_date>2026-05-27T09:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694817</loc>
  <lastmod>2026-05-27T09:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平学習における差別影響の検定と信頼区間（Confidence Intervals for Testing Disparate Impact in Fair Learning）</news:title>
   <news:publication_date>2026-05-27T09:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694815</loc>
  <lastmod>2026-05-27T09:50:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な深い表現は学習可能か（Are Efficient Deep Representations Learnable?）</news:title>
   <news:publication_date>2026-05-27T09:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694813</loc>
  <lastmod>2026-05-27T09:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽譜を聞き、読み、追従する学習（Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game）</news:title>
   <news:publication_date>2026-05-27T09:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694811</loc>
  <lastmod>2026-05-27T08:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度写真生成における自己点検型VAEの革新（IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis）</news:title>
   <news:publication_date>2026-05-27T08:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694809</loc>
  <lastmod>2026-05-27T08:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ビット列で実現する最大・最小回路の設計と解析（Design and Analysis of Efficient Maximum/Minimum Circuits for Stochastic Computing）</news:title>
   <news:publication_date>2026-05-27T08:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694807</loc>
  <lastmod>2026-05-27T08:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイオテンポラル畳み込みニューラルネットワークによる磁気共鳴フィンガープリンティング再構成（Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-27T08:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694805</loc>
  <lastmod>2026-05-27T08:46:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SGDとランダム特徴による学習（Learning with SGD and Random Features）</news:title>
   <news:publication_date>2026-05-27T08:46:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694803</loc>
  <lastmod>2026-05-27T08:46:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電池劣化予測の汎用モデル化（Battery health prediction under generalized conditions using a Gaussian process transition model）</news:title>
   <news:publication_date>2026-05-27T08:46:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694801</loc>
  <lastmod>2026-05-27T08:45:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全方位画像のサリエンシーマップ推定における先行分布の考慮（Saliency Map Estimation for Omni-Directional Image Considering Prior Distributions）</news:title>
   <news:publication_date>2026-05-27T08:45:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694799</loc>
  <lastmod>2026-05-27T08:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチテナント向けクロススライス資源オーケストレーション（Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-27T08:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694797</loc>
  <lastmod>2026-05-27T07:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Knowledge-aware Autoencodersによる説明可能なレコメンダ（Knowledge-aware Autoencoders for Explainable Recommender Sytems）</news:title>
   <news:publication_date>2026-05-27T07:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694795</loc>
  <lastmod>2026-05-27T07:54:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GeoDesc：幾何学的制約を統合した局所記述子学習（GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints）</news:title>
   <news:publication_date>2026-05-27T07:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694793</loc>
  <lastmod>2026-05-27T07:53:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロンの非線形性を学習するカーネルベース深層ニューラルネットワーク（Learning Neuron Non-Linearities with Kernel-Based Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-27T07:53:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694791</loc>
  <lastmod>2026-05-27T07:53:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルベーグ積分に基づく新しい求積法（On Lebesgue Integral Quadrature）</news:title>
   <news:publication_date>2026-05-27T07:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694789</loc>
  <lastmod>2026-05-27T07:53:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>撮像プロトコルの違いに強いドメイン適応（Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on Diffusion-Weighted MR Images）</news:title>
   <news:publication_date>2026-05-27T07:53:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694787</loc>
  <lastmod>2026-05-27T07:52:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散アルゴリズムのスパース化と大規模グラフ処理の新境地（Sparsifying Distributed Algorithms）</news:title>
   <news:publication_date>2026-05-27T07:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694785</loc>
  <lastmod>2026-05-27T07:52:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPhase: 白内障手術動画における手術工程認識（DeepPhase: Surgical Phase Recognition in CATARACTS Videos）</news:title>
   <news:publication_date>2026-05-27T07:52:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694783</loc>
  <lastmod>2026-05-27T07:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチタスク学習によるCTCベース音声認識の改善（HIERARCHICAL MULTITASK LEARNING FOR CTC-BASED SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-05-27T07:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694781</loc>
  <lastmod>2026-05-27T07:00:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波クラウドRANにおける多経路伝送スケジューリング（Multipath Transmission Scheduling in Millimeter Wave Cloud Radio Access Networks）</news:title>
   <news:publication_date>2026-05-27T07:00:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694779</loc>
  <lastmod>2026-05-27T06:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報源融合と最適化によるICMEの実現（Multi-Information Source Fusion and Optimization to Realize ICME: Application to Dual Phase Materials）</news:title>
   <news:publication_date>2026-05-27T06:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694777</loc>
  <lastmod>2026-05-27T06:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルール行列による説明可能な機械学習の可視化（RuleMatrix: The Visual Interface）</news:title>
   <news:publication_date>2026-05-27T06:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694775</loc>
  <lastmod>2026-05-27T06:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用拡散過程を学習することによる画像復元の効率化（Learning Generic Diffusion Processes for Image Restoration）</news:title>
   <news:publication_date>2026-05-27T06:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694773</loc>
  <lastmod>2026-05-27T06:58:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノックオフ手法による特徴重要度の統計と偽発見率保証（Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees）</news:title>
   <news:publication_date>2026-05-27T06:58:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694771</loc>
  <lastmod>2026-05-27T06:57:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーティッド情報融合による堅牢なマルチモーダル学習（Robust Deep Multi-modal Learning Based on Gated Information Fusion Network）</news:title>
   <news:publication_date>2026-05-27T06:57:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694769</loc>
  <lastmod>2026-05-27T06:06:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Planck 2018が残した宇宙論の遺産（Planck 2018 results. I. Overview and the cosmological legacy of Planck）</news:title>
   <news:publication_date>2026-05-27T06:06:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694767</loc>
  <lastmod>2026-05-27T06:05:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的イメージングデータのための罰則付き行列分解（Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data）</news:title>
   <news:publication_date>2026-05-27T06:05:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694765</loc>
  <lastmod>2026-05-27T06:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯型マルチメディア翻訳による食事管理支援（A Hand-Held Multimedia Translation and Interpretation System with Application to Diet Management）</news:title>
   <news:publication_date>2026-05-27T06:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694763</loc>
  <lastmod>2026-05-27T06:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPIRIT望遠鏡イニシアティブ──教育用ウェブ対応ロボット望遠鏡の6年間の教訓（The SPIRIT Telescope Initiative: six years on）</news:title>
   <news:publication_date>2026-05-27T06:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694761</loc>
  <lastmod>2026-05-27T06:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFi接続ログからプライバシーを守りつつ行動パターンを識別する手法 (Privacy-preserving classifiers recognize shared mobility behaviours from WiFi network imperfect data)</news:title>
   <news:publication_date>2026-05-27T06:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694759</loc>
  <lastmod>2026-05-27T06:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別的アプローチによるベイズフィルタリングとその応用（A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding）</news:title>
   <news:publication_date>2026-05-27T06:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694757</loc>
  <lastmod>2026-05-27T06:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>送電系統における植生起因停電の予測手法（A Data-Driven Approach for Predicting Vegetation-Related Outages in Power Distribution Systems）</news:title>
   <news:publication_date>2026-05-27T06:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694755</loc>
  <lastmod>2026-05-27T05:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非適応条件付きサンプリングを用いた分布検定アルゴリズム（Anaconda: A Non-Adaptive Conditional Sampling Algorithm for Distribution Testing）</news:title>
   <news:publication_date>2026-05-27T05:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694753</loc>
  <lastmod>2026-05-27T05:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小問い合わせで学ぶ凸分割と均衡計算（Learning Convex Partitions and Computing Game-theoretic Equilibria from Best Response Queries）</news:title>
   <news:publication_date>2026-05-27T05:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694751</loc>
  <lastmod>2026-05-27T05:07:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な推薦のための層別関連度伝播（Layer-wise Relevance Propagation for Explainable Recommendations）</news:title>
   <news:publication_date>2026-05-27T05:07:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694749</loc>
  <lastmod>2026-05-27T05:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Horn包のPAC学習（Probably approximately correct learning of Horn envelopes from queries）</news:title>
   <news:publication_date>2026-05-27T05:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694747</loc>
  <lastmod>2026-05-27T05:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続行動空間における線形計算量の離散化によるQ学習の拡張（DISCRETE LINEAR-COMPLEXITY REINFORCEMENT LEARNING IN CONTINUOUS ACTION SPACES FOR Q-LEARNING ALGORITHMS）</news:title>
   <news:publication_date>2026-05-27T05:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694745</loc>
  <lastmod>2026-05-27T05:07:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー材料の性質を機械学習で予測する（Machine Learning of Energetic Material Properties）</news:title>
   <news:publication_date>2026-05-27T05:07:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694743</loc>
  <lastmod>2026-05-27T05:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察のみから模倣する生成的敵対学習（Generative Adversarial Imitation from Observation）</news:title>
   <news:publication_date>2026-05-27T05:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694741</loc>
  <lastmod>2026-05-27T04:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約ベースの視覚生成（Constraint-Based Visual Generation）</news:title>
   <news:publication_date>2026-05-27T04:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694739</loc>
  <lastmod>2026-05-27T04:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列を考慮したLSTMによる放射線異常の縦断検出（Longitudinal detection of radiological abnormalities with time-modulated LSTM）</news:title>
   <news:publication_date>2026-05-27T04:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694737</loc>
  <lastmod>2026-05-27T04:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓpに基づく低ランク近似のPTAS登場（A PTAS for ℓp-Low Rank Approximation）</news:title>
   <news:publication_date>2026-05-27T04:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694735</loc>
  <lastmod>2026-05-27T04:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大質量比二体ブラックホール合体の大規模並列シミュレーション（Massively Parallel Simulations of Binary Black Hole Intermediate-Mass-Ratio Inspirals）</news:title>
   <news:publication_date>2026-05-27T04:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694733</loc>
  <lastmod>2026-05-27T04:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データの有効活用による都市景観セマンティックセグメンテーション（Effective Use of Synthetic Data for Urban Scene Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-27T04:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694731</loc>
  <lastmod>2026-05-27T04:12:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>否定表現を見落とすな：Twitter顧客対応会話における否定処理を組み込んだ対話行為予測（Don’t get Lost in Negation: An Effective Negation Handled Dialogue Acts Prediction Algorithm for Twitter Customer Service Conversations）</news:title>
   <news:publication_date>2026-05-27T04:12:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694729</loc>
  <lastmod>2026-05-27T04:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループにおける顔レベルの相互作用解析が示すもの（Computational Social Dynamics: Analyzing the Face-level Interactions in a Group）</news:title>
   <news:publication_date>2026-05-27T04:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694727</loc>
  <lastmod>2026-05-27T03:20:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高階確率プログラムの形式検証（Formal Verification of Higher-Order Probabilistic Programs）</news:title>
   <news:publication_date>2026-05-27T03:20:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694725</loc>
  <lastmod>2026-05-27T03:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的状態を用いた予後推定（Prognostics Estimations with Dynamic States）</news:title>
   <news:publication_date>2026-05-27T03:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694723</loc>
  <lastmod>2026-05-27T03:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的シールドによる安全な強化学習（Safe Reinforcement Learning via Probabilistic Shields）</news:title>
   <news:publication_date>2026-05-27T03:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694721</loc>
  <lastmod>2026-05-27T03:19:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済み3D物体検出モデルを用いた高速グラウンドトゥルース生成（Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation）</news:title>
   <news:publication_date>2026-05-27T03:19:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694719</loc>
  <lastmod>2026-05-27T03:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-27T03:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694717</loc>
  <lastmod>2026-05-27T03:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線における弱教師あり深層学習による疾患分類と局所化（Weakly Supervised Deep Learning for Thoracic Disease Classification and Localization on Chest X-rays）</news:title>
   <news:publication_date>2026-05-27T03:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694715</loc>
  <lastmod>2026-05-27T03:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キロディグリーサーベイによる銀河のサイズ―恒星質量関係の進化（Evolution of galaxy size–stellar mass relation from the Kilo Degree Survey）</news:title>
   <news:publication_date>2026-05-27T03:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694713</loc>
  <lastmod>2026-05-27T02:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の敵対者が存在する環境下でのオンライン頑健方策学習（Online Robust Policy Learning in the Presence of Unknown Adversaries）</news:title>
   <news:publication_date>2026-05-27T02:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-27T02:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-27T02:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694707</loc>
  <lastmod>2026-05-27T02:26:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Unlimited Road-scene Synthetic Annotation（Unlimited Road-scene Synthetic Annotation (URSA) Dataset）</news:title>
   <news:publication_date>2026-05-27T02:26:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694705</loc>
  <lastmod>2026-05-27T02:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-27T02:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694703</loc>
  <lastmod>2026-05-27T02:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論的距離測度と双方向Helmholtzマシン（On the Information Theoretic Distance Measures and Bidirectional Helmholtz Machines）</news:title>
   <news:publication_date>2026-05-27T02:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694701</loc>
  <lastmod>2026-05-27T02:25:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変質量系に対するニュートンの第二法則に関する考察（Remarks on Newton’s Second Law for Variable Mass Systems）</news:title>
   <news:publication_date>2026-05-27T02:25:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694699</loc>
  <lastmod>2026-05-27T01:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習で新物理を見つける道案内（Guiding New Physics Searches with Unsupervised Learning）</news:title>
   <news:publication_date>2026-05-27T01:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694697</loc>
  <lastmod>2026-05-27T01:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pangloss: ノイズの多いテキスト環境における高速エンティティリンク（Pangloss: Fast Entity Linking in Noisy Text Environments）</news:title>
   <news:publication_date>2026-05-27T01:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694695</loc>
  <lastmod>2026-05-27T01:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックホールのアルファビットを学ぶ（Learning the Alpha-bits of Black Holes）</news:title>
   <news:publication_date>2026-05-27T01:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694693</loc>
  <lastmod>2026-05-27T01:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校における企業型ソーシャルネットワークの学習手法と安全性（Methods, Forms and Safety of Learning in Corporate Social Networks）</news:title>
   <news:publication_date>2026-05-27T01:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694691</loc>
  <lastmod>2026-05-27T01:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子ソーシャルネットワークにおける生徒の教授法の進化（The Evolution of Teaching Methods of Students in Electronic Social Networks）</news:title>
   <news:publication_date>2026-05-27T01:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694689</loc>
  <lastmod>2026-05-27T01:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低表面輝度銀河のHST撮像が示したこと（The Dragonfly Nearby Galaxies Survey. V. HST Imaging）</news:title>
   <news:publication_date>2026-05-27T01:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694687</loc>
  <lastmod>2026-05-27T01:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジを意識した点群統合の新展開（EC-Net: an Edge-aware Point set Consolidation Network）</news:title>
   <news:publication_date>2026-05-27T01:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694685</loc>
  <lastmod>2026-05-27T00:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非正規教育におけるクラウドサービスを用いた教員の専門能力開発（Professional Development of Teachers Using Cloud Services During Non-formal Education）</news:title>
   <news:publication_date>2026-05-27T00:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694683</loc>
  <lastmod>2026-05-27T00:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一段階・単一フェーズで行う肺結節検出の新展開（Towards Single-phase Single-stage Detection of Pulmonary Nodules in Chest CT Imaging）</news:title>
   <news:publication_date>2026-05-27T00:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694681</loc>
  <lastmod>2026-05-27T00:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮画像での複数ラベル式歩行者検出の実用化可能性（Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection）</news:title>
   <news:publication_date>2026-05-27T00:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694679</loc>
  <lastmod>2026-05-27T00:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/694677</loc>
  <lastmod>2026-05-27T00:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-27T00:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子QCD観測量のための機械学習推定器（Machine learning estimators for lattice QCD observables）</news:title>
   <news:publication_date>2026-05-27T00:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694673</loc>
  <lastmod>2026-05-27T00:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動ステレオ用エンドツーエンド自己教師あり学習（ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems）</news:title>
   <news:publication_date>2026-05-27T00:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694671</loc>
  <lastmod>2026-05-26T23:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二足歩行ロボットの強化学習による自律歩行（Bipedal Walking Robot using Deep Deterministic Policy Gradient）</news:title>
   <news:publication_date>2026-05-26T23:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694669</loc>
  <lastmod>2026-05-26T23:35:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ATLAS ITk向け CMOSピクセルセンサー試作の実性能評価（Performance of CMOS pixel sensor prototypes in ams H35 and aH18 technology for the ATLAS ITk upgrade）</news:title>
   <news:publication_date>2026-05-26T23:35:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694667</loc>
  <lastmod>2026-05-26T23:35:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合リスクを伴うシアミーズ生存解析（Siamese Survival Analysis with Competing Risks）</news:title>
   <news:publication_date>2026-05-26T23:35:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694665</loc>
  <lastmod>2026-05-26T23:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能な遺伝子制御ネットワークの進化（Evolving Differentiable Gene Regulatory Networks）</news:title>
   <news:publication_date>2026-05-26T23:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694663</loc>
  <lastmod>2026-05-26T23:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分推論による生成モデルの統一的枠組み（Variational Inference: A Unified Framework of Generative Models and Some Revelations）</news:title>
   <news:publication_date>2026-05-26T23:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694661</loc>
  <lastmod>2026-05-26T23:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロパネルデータの特徴量ベースクラスタリング手法の要点（Novel Feature-Based Clustering of Micro-Panel Data (CluMP))</news:title>
   <news:publication_date>2026-05-26T23:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694659</loc>
  <lastmod>2026-05-26T23:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IFUデータキューブからの高速自動スペクトル抽出ソフト AutoSpec（AutoSpec: Fast Automated Spectral Extraction Software for IFU Datacubes）</news:title>
   <news:publication_date>2026-05-26T23:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694657</loc>
  <lastmod>2026-05-26T22:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリープ分割におけるCNNの不確実性モデル化と解釈可能性（UNCERTAINTY MODELING AND INTERPRETABILITY IN CONVOLUTIONAL NEURAL NETWORKS FOR POLYP SEGMENTATION）</news:title>
   <news:publication_date>2026-05-26T22:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694655</loc>
  <lastmod>2026-05-26T22:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データへのドメインランダム化適用による物体カテゴリ検出（Applying Domain Randomization to Synthetic Data for Object Category Detection）</news:title>
   <news:publication_date>2026-05-26T22:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694653</loc>
  <lastmod>2026-05-26T22:42:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の「驚き」の知覚を測る──計算モデルは人を驚かせられるか（Human Perception of Surprise: A User Study）</news:title>
   <news:publication_date>2026-05-26T22:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694651</loc>
  <lastmod>2026-05-26T22:42:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドな音楽推薦の機械学習アプローチ（Machine Learning Approaches to Hybrid Music Recommender Systems）</news:title>
   <news:publication_date>2026-05-26T22:42:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694649</loc>
  <lastmod>2026-05-26T22:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な深層強化学習への道（Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees）</news:title>
   <news:publication_date>2026-05-26T22:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694647</loc>
  <lastmod>2026-05-26T22:41:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット学習に基づく物体関係検出（Object Relation Detection Based on One-shot Learning）</news:title>
   <news:publication_date>2026-05-26T22:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694645</loc>
  <lastmod>2026-05-26T22:41:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メンバーシッププライバシーを守る対抗的正則化（Machine Learning with Membership Privacy using Adversarial Regularization）</news:title>
   <news:publication_date>2026-05-26T22:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694643</loc>
  <lastmod>2026-05-26T21:50:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布の「場」を守る敵対的学習の提案（Manifold Adversarial Learning）</news:title>
   <news:publication_date>2026-05-26T21:50:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694641</loc>
  <lastmod>2026-05-26T21:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験を記憶し忘れることで経験再生を改善する（Remember and Forget for Experience Replay）</news:title>
   <news:publication_date>2026-05-26T21:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694639</loc>
  <lastmod>2026-05-26T21:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中動画から魚の個体数を自動推定する技術の意義（Assessing fish abundance from underwater video using deep neural networks）</news:title>
   <news:publication_date>2026-05-26T21:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694637</loc>
  <lastmod>2026-05-26T21:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮したニューラルネットワークと雑音除去オートエンコーダの組合せによる文字列類似度測定 (Combining a Context Aware Neural Network with a Denoising Autoencoder for Measuring String Similarities)</news:title>
   <news:publication_date>2026-05-26T21:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694635</loc>
  <lastmod>2026-05-26T21:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い準障壁での軽核融合反応における天体物理学的S因子（Astrophysical S-factor for the deep sub-barrier fusion reactions of light nuclei）</news:title>
   <news:publication_date>2026-05-26T21:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694633</loc>
  <lastmod>2026-05-26T21:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動音響鳥類検出と深層学習の実証（Automatic acoustic detection of birds through deep learning）</news:title>
   <news:publication_date>2026-05-26T21:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694631</loc>
  <lastmod>2026-05-26T21:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種複雑性を持つデータに強い無正則化スコアによる異常検知（Deep Generative Model using Unregularized Score for Anomaly Detection with Heterogeneous Complexity）</news:title>
   <news:publication_date>2026-05-26T21:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694629</loc>
  <lastmod>2026-05-26T20:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分光イメージングによる顔認証の現状と課題（An Extensive Review on Spectral Imaging in Biometric Systems: Challenges &amp;amp; Advancements）</news:title>
   <news:publication_date>2026-05-26T20:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694627</loc>
  <lastmod>2026-05-26T20:57:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時系列相乗残差学習によるビデオ人物再識別（Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification）</news:title>
   <news:publication_date>2026-05-26T20:57:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694625</loc>
  <lastmod>2026-05-26T20:57:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1550nm帯におけるPAM‑4伝送とフォトニック・リザバーコンピューティングによる後処理（PAM-4 Transmission at 1550nm using Photonic Reservoir Computing Post-processing）</news:title>
   <news:publication_date>2026-05-26T20:57:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694623</loc>
  <lastmod>2026-05-26T20:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報流を手がかりにCNNを大幅圧縮するBRIEF（Backward Reduction of CNNs with Information Flow Analysis）</news:title>
   <news:publication_date>2026-05-26T20:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694621</loc>
  <lastmod>2026-05-26T20:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の相対論的流体力学への応用（Applications of deep learning to relativistic hydrodynamics）</news:title>
   <news:publication_date>2026-05-26T20:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694619</loc>
  <lastmod>2026-05-26T20:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程を用いた確率微分方程式の学習（Learning Stochastic Differential Equations with Gaussian Processes without Gradient Matching）</news:title>
   <news:publication_date>2026-05-26T20:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694617</loc>
  <lastmod>2026-05-26T20:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トップN推薦のための集合的変分オートエンコーダ（A Collective Variational Autoencoder for Top-N Recommendation with Side Information）</news:title>
   <news:publication_date>2026-05-26T20:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694615</loc>
  <lastmod>2026-05-26T20:05:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的結合デモザイキングとノイズ除去：Residual Denoising Networkによる画像復元（Iterative Joint Image Demosaicking and Denoising using a Residual Denoising Network）</news:title>
   <news:publication_date>2026-05-26T20:05:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694613</loc>
  <lastmod>2026-05-26T20:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の統治——安全・責任・プライバシー・サイバーセキュリティと産業リスクへの新たな対応（Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks）</news:title>
   <news:publication_date>2026-05-26T20:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694611</loc>
  <lastmod>2026-05-26T20:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載エッジコンピューティングにおけるタスク複製と学習による遅延最小化（Task Replication for Vehicular Edge Computing: A Combinatorial Multi-Armed Bandit based Approach）</news:title>
   <news:publication_date>2026-05-26T20:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694609</loc>
  <lastmod>2026-05-26T20:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度リモートセンシング画像の土地被覆分類と転移可能な深層モデルの適用 (Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models)</news:title>
   <news:publication_date>2026-05-26T20:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694607</loc>
  <lastmod>2026-05-26T20:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>End-to-end Neural Geometryによる頑健な深度・姿勢推定（End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs）</news:title>
   <news:publication_date>2026-05-26T20:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694605</loc>
  <lastmod>2026-05-26T20:03:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RESCAN: 単一画像の雨除去に向けた再帰的SE文脈集約ネットワーク（Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining）</news:title>
   <news:publication_date>2026-05-26T20:03:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694603</loc>
  <lastmod>2026-05-26T20:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNet50で抽出した特徴をDeepForestで分類する皮膚病変判定手法（Disease Classification within Dermascopic Images Using features extracted by ResNet50 and classification through DeepForest）</news:title>
   <news:publication_date>2026-05-26T20:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694601</loc>
  <lastmod>2026-05-26T19:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン学習による風力発電予測の革新（Scene Learning: Deep Convolutional Networks For Wind Power Prediction by Embedding Turbines into Grid Space）</news:title>
   <news:publication_date>2026-05-26T19:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694599</loc>
  <lastmod>2026-05-26T19:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ人物再識別のための自己・協調注意ネットワーク（SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification）</news:title>
   <news:publication_date>2026-05-26T19:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694597</loc>
  <lastmod>2026-05-26T19:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で可視化する銀河形態の隠れた特徴（Visualizing the Hidden Features of Galaxy Morphology with Machine Learning）</news:title>
   <news:publication_date>2026-05-26T19:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694595</loc>
  <lastmod>2026-05-26T19:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー記述子による点群の整合化を高める手法（Learning and Matching Multi-View Descriptors for Registration of Point Clouds）</news:title>
   <news:publication_date>2026-05-26T19:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694593</loc>
  <lastmod>2026-05-26T19:11:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNSトラフィックの時系列デインターリービング（Time Series Deinterleaving of DNS Traffic）</news:title>
   <news:publication_date>2026-05-26T19:11:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694591</loc>
  <lastmod>2026-05-26T19:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みスパースカーネルネットワーク（Convolutional Sparse Kernel Network for Unsupervised Medical Image Analysis）</news:title>
   <news:publication_date>2026-05-26T19:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694589</loc>
  <lastmod>2026-05-26T19:10:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル間フロー類似度による自己教師あり学習（Cross Pixel Optical Flow Similarity for Self-Supervised Learning）</news:title>
   <news:publication_date>2026-05-26T19:10:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694587</loc>
  <lastmod>2026-05-26T18:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム平滑化による効率的なファジング（NEUZZ: Efficient Fuzzing with Neural Program Smoothing）</news:title>
   <news:publication_date>2026-05-26T18:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694585</loc>
  <lastmod>2026-05-26T18:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索とレコメンデーションの共同最適化が変える現場（Joint Modeling and Optimization of Search and Recommendation）</news:title>
   <news:publication_date>2026-05-26T18:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694583</loc>
  <lastmod>2026-05-26T18:19:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顕著性とセマンティックパーシングを併用した人物再識別の改良（Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network Models）</news:title>
   <news:publication_date>2026-05-26T18:19:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694581</loc>
  <lastmod>2026-05-26T18:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非圧縮乱流におけるモデル由来の不確かさの特徴付け（CHARACTERIZATION OF MODEL-BASED UNCERTAINTIES IN INCOMPRESSIBLE TURBULENT FLOWS BY MACHINE LEARNING）</news:title>
   <news:publication_date>2026-05-26T18:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694579</loc>
  <lastmod>2026-05-26T18:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限ハードウェアでの意味的セグメンテーションの深層学習（Deep Learning for Semantic Segmentation on Minimal Hardware）</news:title>
   <news:publication_date>2026-05-26T18:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694577</loc>
  <lastmod>2026-05-26T18:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノスケール導波路におけるフォノン‐ポラリトンとBrillouin誘起透過・不透過（Phonon-Polaritons in Nanoscale Waveguides）</news:title>
   <news:publication_date>2026-05-26T18:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694575</loc>
  <lastmod>2026-05-26T18:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク神経科学による脳–コンピュータ・インターフェース最適化（Network neuroscience for optimizing brain-computer interfaces）</news:title>
   <news:publication_date>2026-05-26T18:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694573</loc>
  <lastmod>2026-05-26T17:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離辞書学習の大域最適化と拡散MRIへの応用（GLOBAL OPTIMALITY IN SEPARABLE DICTIONARY LEARNING WITH APPLICATIONS TO THE ANALYSIS OF DIFFUSION MRI）</news:title>
   <news:publication_date>2026-05-26T17:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694571</loc>
  <lastmod>2026-05-26T17:26:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化された低消費電力IoTネットワーク：分散学習アプローチ（Self-organized Low-power IoT Networks: A Distributed Learning Approach）</news:title>
   <news:publication_date>2026-05-26T17:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694569</loc>
  <lastmod>2026-05-26T17:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし視覚特徴のためのディープクラスタリング（Deep Clustering for Unsupervised Learning of Visual Features）</news:title>
   <news:publication_date>2026-05-26T17:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694567</loc>
  <lastmod>2026-05-26T17:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で組合せ問題のモデリングを強化する（Boosting Combinatorial Problem Modeling with Machine Learning）</news:title>
   <news:publication_date>2026-05-26T17:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694565</loc>
  <lastmod>2026-05-26T17:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepInfによるソーシャル影響予測の革新（DeepInf: Social Influence Prediction with Deep Learning）</news:title>
   <news:publication_date>2026-05-26T17:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694563</loc>
  <lastmod>2026-05-26T17:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続値を含む確率的論理プログラムの学習（Learning Probabilistic Logic Programs in Continuous Domains）</news:title>
   <news:publication_date>2026-05-26T17:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694561</loc>
  <lastmod>2026-05-26T16:34:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる物体検出の総説（Object Detection with Deep Learning: A Review）</news:title>
   <news:publication_date>2026-05-26T16:34:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694559</loc>
  <lastmod>2026-05-26T16:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模推薦で振れ幅を個別制御する手法（Magnitude Bounded Matrix Factorisation for Recommender Systems）</news:title>
   <news:publication_date>2026-05-26T16:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694557</loc>
  <lastmod>2026-05-26T16:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ttH（トップクォーク対付随Higgs）探索の要点と経営判断への示唆（Searches for ttH production at CMS）</news:title>
   <news:publication_date>2026-05-26T16:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694555</loc>
  <lastmod>2026-05-26T16:33:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド領域における効率的な問合せと学習（Tractable Querying and Learning in Hybrid Domains via Sum-Product Networks）</news:title>
   <news:publication_date>2026-05-26T16:33:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694553</loc>
  <lastmod>2026-05-26T16:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張とバギングによる深層ニューラルネットワークアンサンブルによる皮膚病変分類 (Deep neural network ensemble by data augmentation and bagging for skin lesion classification)</news:title>
   <news:publication_date>2026-05-26T16:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694551</loc>
  <lastmod>2026-05-26T16:32:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり特徴学習による筆跡識別の改善（Semi-supervised Feature Learning For Improving Writer Identification）</news:title>
   <news:publication_date>2026-05-26T16:32:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694549</loc>
  <lastmod>2026-05-26T16:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近リアルタイム海馬領域セグメンテーション（Near Real-time Hippocampus Segmentation Using Patch-based Canonical Neural Network）</news:title>
   <news:publication_date>2026-05-26T16:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694547</loc>
  <lastmod>2026-05-26T15:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタイムホライズンの太陽光予測を統一的に行う手法（Multi-time-horizon Solar Forecasting Using Recurrent Neural Network）</news:title>
   <news:publication_date>2026-05-26T15:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694545</loc>
  <lastmod>2026-05-26T15:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層強化学習によるマルチエージェント航行（Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation）</news:title>
   <news:publication_date>2026-05-26T15:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694543</loc>
  <lastmod>2026-05-26T15:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>北天における極度逆転スペクトル外部銀河電波源の探索（Towards building a first northern-sky sample of ‘Extremely Inverted Spectrum Extragalactic Radio Sources (EISERS)’）</news:title>
   <news:publication_date>2026-05-26T15:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694541</loc>
  <lastmod>2026-05-26T15:40:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度マップからの3D人体姿勢推定――深度を用いたプロトタイプ線形結合によるアプローチ（3D human pose estimation from depth maps using a deep combination of poses）</news:title>
   <news:publication_date>2026-05-26T15:40:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694539</loc>
  <lastmod>2026-05-26T15:40:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース緩和正則化回帰の統一フレームワーク（A Unified Framework for Sparse Relaxed Regularized Regression: SR3）</news:title>
   <news:publication_date>2026-05-26T15:40:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694537</loc>
  <lastmod>2026-05-26T15:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションと部分的教師あり学習による3次元ハンドポーズ推定（3D Hand Pose Estimation using Simulation and Partial-Supervision with a Shared Latent Space）</news:title>
   <news:publication_date>2026-05-26T15:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694535</loc>
  <lastmod>2026-05-26T15:39:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMath用フィルタの開発とMoodle統合（Development of SageMath filter for Moodle）</news:title>
   <news:publication_date>2026-05-26T15:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
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