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   <news:title>単語レベル損失による時系列関係分類の改善（Word-Level Loss Extensions for Neural Temporal Relation Classification）</news:title>
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   <news:title>腫瘍組織における細胞分類で「空間の文脈」を取り込む意義（Capturing global spatial context for accurate cell classification in skin cancer histology）</news:title>
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   <news:title>ワイヤレス通信におけるエンドツーエンド深層学習の応用（Application of End-to-End Deep Learning in Wireless Communications Systems）</news:title>
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   <news:title>深層ニューラルネットワークによるエンコーダ・デコーダ構築（Building Encoder and Decoder with Deep Neural Networks: On the Way to Reality）</news:title>
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   <news:title>表情から学習への没入度を自動認識する深層学習（Automatic Recognition of Student Engagement using Deep Learning）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>機械学習の超かんたん入門と通信システムへの応用（A Very Brief Introduction to Machine Learning With Applications to Communication Systems）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>強化回帰による最適停止問題の数値解法（Optimal stopping via reinforced regression）</news:title>
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   <news:title>都市環境におけるFaster R-CNNベースの二輪検出と分類（Motorcycle detection and classification in urban Scenarios using a model based on Faster R-CNN）</news:title>
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   <news:title>抽象スケッチの逆変換と輪郭・詳細の因子分解（Deep Factorised Inverse-Sketching）</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>グループデータ解析における信号の隠れ構造モデリング（Modelling hidden structure of signals in group data analysis with modified (Lr, 1) and block-term decompositions）</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>ソーシャルメディアにおける発話役割分類（How did the discussion go: Discourse act classification in social media conversations）</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>マルチ出力畳み込みスペクトル混合カーネル（Multi-Output Convolution Spectral Mixture for Gaussian Processes）</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>クラウド資源の性能意識型管理──分類と今後の方向性（Performance-Aware Management of Cloud Resources: A Taxonomy and Future Directions）</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>深層積層確率的構成ネットワークによる非定常データストリームの継続学習（DEEP STACKED STOCHASTIC CONFIGURATION NETWORKS FOR LIFELONG LEARNING OF NON-STATIONARY DATA STREAMS）</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>非持続的ストラグラーを利用した分散勾配降下の高速化（Speeding Up Distributed Gradient Descent by Utilizing Non-persistent Stragglers）</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>DeePathologyが示したがんの分子診断統合の道筋（DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome）</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>堅牢な返金政策（Robust Refund Policy）</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>平均連結法を超える階層クラスタリング（Hierarchical Clustering better than Average-Linkage）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>セグメンタル音声Word2Vecによる発話表現（SEGMENTAL AUDIO WORD2VEC: REPRESENTING UTTERANCES AS SEQUENCES OF VECTORS WITH APPLICATIONS IN SPOKEN TERM DETECTION）</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>Grassmann多様体を利用した学習の位置づけと応用（Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/697109</loc>
  <lastmod>2026-06-02T15:37:56Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>移動体ミリ波システムにおけるチャネル共分散行列の生成的推定（Generative Adversarial Estimation of Channel Covariance in Vehicular Millimeter Wave Systems）</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>超解像でMRIを高速化し定量バイオマーカーを同時取得する可能性（Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging）</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>視覚的感情のデータ偏りを考察する（Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias）</news:title>
   <news:publication_date>2026-06-02T15:37:32Z</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>
   </news:publication>
   <news:title>科学・工学応用における機械学習の数学的基盤の重要性（Importance of the Mathematical Foundations of Machine Learning Methods for Scientific and Engineering Applications）</news:title>
   <news:publication_date>2026-06-02T15:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/697101</loc>
  <lastmod>2026-06-02T14:45:28Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>予測制御と深層学習を組み合わせたヒト動作追従（Deep Learning with Predictive Control for Human Motion Tracking）</news:title>
   <news:publication_date>2026-06-02T14:45:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/697099</loc>
  <lastmod>2026-06-02T14:44:52Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ローカル差分プライバシー下の分布検定（Test without Trust: Optimal Locally Private Distribution Testing）</news:title>
   <news:publication_date>2026-06-02T14:44:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/697097</loc>
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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>事例依存型PU学習のベイズ最適再ラベリング（Instance-Dependent PU Learning by Bayesian Optimal Relabeling）</news:title>
   <news:publication_date>2026-06-02T14:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/697095</loc>
  <lastmod>2026-06-02T14:44:13Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>窒素中間錯体がGaAs1−xNx合金の電子特性に与える影響（Effect of N interstitial complexes on the electronic properties of GaAs1−xNx alloys from first principles）</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>確率的バッチサイズを用いた高速分散削減法（Fast Variance Reduction Method with Stochastic Batch Size）</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>ICUに入院したがん患者の生存率改善（Improved survival of cancer patients admitted to the ICU between 2002 and 2011）</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>スパースかつ補完的な畳み込みの効率的融合（Efficient Fusion of Sparse and Complementary Convolutions）</news:title>
   <news:publication_date>2026-06-02T14:43:08Z</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>
   </news:publication>
   <news:title>注意を用いた意味対応とオフセット認識相関カーネル（Attentive Semantic Alignment with Offset-Aware Correlation Kernels）</news:title>
   <news:publication_date>2026-06-02T13:52:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697085</loc>
  <lastmod>2026-06-02T13:51:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会影響の確率的因果分析（Probabilistic Causal Analysis of Social Influence）</news:title>
   <news:publication_date>2026-06-02T13:51:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697083</loc>
  <lastmod>2026-06-02T13:50:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係ロジスティック回帰の構造学習（Structure Learning for Relational Logistic Regression: An Ensemble Approach）</news:title>
   <news:publication_date>2026-06-02T13:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697081</loc>
  <lastmod>2026-06-02T13:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Non-Learning based Deep Parallel MRI Reconstruction（Non-Learning based Deep Parallel MRI Reconstruction）</news:title>
   <news:publication_date>2026-06-02T13:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697079</loc>
  <lastmod>2026-06-02T13:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ不確実性とモデル感度に基づく能動学習（Active Learning based on Data Uncertainty and Model Sensitivity）</news:title>
   <news:publication_date>2026-06-02T13:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697077</loc>
  <lastmod>2026-06-02T13:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意を注視する――系列解析における影響あるサンプルの可視化（Paying Attention to Attention: Highlighting Influential Samples in Sequential Analysis）</news:title>
   <news:publication_date>2026-06-02T13:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697075</loc>
  <lastmod>2026-06-02T13:48:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似解の誤差を機械学習で定量化する手法（Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations）</news:title>
   <news:publication_date>2026-06-02T13:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697065</loc>
  <lastmod>2026-06-02T12:57:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意図の共有と隠蔽を学習する情報正則化（Learning to Share and Hide Intentions using Information Regularization）</news:title>
   <news:publication_date>2026-06-02T12:57:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697063</loc>
  <lastmod>2026-06-02T12:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド表現による深層生成的シーン合成（Deep Generative Modeling for Scene Synthesis via Hybrid Representations）</news:title>
   <news:publication_date>2026-06-02T12:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697061</loc>
  <lastmod>2026-06-02T12:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミングデータの高速主成分部分空間投影（Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching）</news:title>
   <news:publication_date>2026-06-02T12:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697059</loc>
  <lastmod>2026-06-02T12:56:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏りのない暗黙的変分推論（Unbiased Implicit Variational Inference）</news:title>
   <news:publication_date>2026-06-02T12:56:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697057</loc>
  <lastmod>2026-06-02T12:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークとテンソルネットワークを架橋するGTMS（Generalized transfer matrix states from artificial neural networks）</news:title>
   <news:publication_date>2026-06-02T12:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697055</loc>
  <lastmod>2026-06-02T12:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データカルキュレータの内部（The Internals of the Data Calculator）</news:title>
   <news:publication_date>2026-06-02T12:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697053</loc>
  <lastmod>2026-06-02T12:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Semblance: 確率空間上の順位ベース・カーネルによるニッチ検出（Semblance: A Rank-Based Kernel on Probability Spaces for Niche Detection）</news:title>
   <news:publication_date>2026-06-02T12:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697051</loc>
  <lastmod>2026-06-02T12:04:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HALOGAS銀河の深掘り：GBTによるH I観測が示す周辺環境の実像（A GBT Survey of the HALOGAS Galaxies and Their Environments I: Revealing the Full Extent of Hi around NGC891, NGC925, NGC4414 &amp;amp; NGC4565）</news:title>
   <news:publication_date>2026-06-02T12:04:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697049</loc>
  <lastmod>2026-06-02T12:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プッシュ通知からの個人知識抽出（Personal Knowledge Extraction from Push Notifications）</news:title>
   <news:publication_date>2026-06-02T12:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697047</loc>
  <lastmod>2026-06-02T12:03:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心室全体のマルチ推定器による定量化（Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning）</news:title>
   <news:publication_date>2026-06-02T12:03:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697045</loc>
  <lastmod>2026-06-02T12:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LED街路灯を用いた太陽光車両検知（Sunlight Enabled Vehicle Detection by LED Street Lights）</news:title>
   <news:publication_date>2026-06-02T12:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697043</loc>
  <lastmod>2026-06-02T12:02:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時エッジ整列と学習（Simultaneous Edge Alignment and Learning）</news:title>
   <news:publication_date>2026-06-02T12:02:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697041</loc>
  <lastmod>2026-06-02T12:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二段階ハッシュ法の再考──Binary Matrix Pursuitによる符号推論の合理化（Hashing with Binary Matrix Pursuit）</news:title>
   <news:publication_date>2026-06-02T12:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697039</loc>
  <lastmod>2026-06-02T12:02:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線給電型モバイルエッジコンピューティングにおけるオンライン計算オフローディングのための深層強化学習（Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks）</news:title>
   <news:publication_date>2026-06-02T12:02:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697037</loc>
  <lastmod>2026-06-02T11:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負行列因子分解に対する代替サロゲート手法の概観（A Survey on Surrogate Approaches to Non-negative Matrix Factorization）</news:title>
   <news:publication_date>2026-06-02T11:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697035</loc>
  <lastmod>2026-06-02T11:10:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層転移学習の概観（A Survey on Deep Transfer Learning）</news:title>
   <news:publication_date>2026-06-02T11:10:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697033</loc>
  <lastmod>2026-06-02T11:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的視覚チャレンジ（Adversarial Vision Challenge）</news:title>
   <news:publication_date>2026-06-02T11:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697031</loc>
  <lastmod>2026-06-02T11:09:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィーを用いた原子核に対する深い非弾性散乱（Deep Inelastic Scattering on a Nucleus using Holography）</news:title>
   <news:publication_date>2026-06-02T11:09:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697029</loc>
  <lastmod>2026-06-02T11:09:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データを差分プライバシーで公開する手法の実務的意義（OptStream: Releasing Time Series Privately）</news:title>
   <news:publication_date>2026-06-02T11:09:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697027</loc>
  <lastmod>2026-06-02T11:09:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部臓器の形状から糖尿病を予測する深層形状解析（Deep Shape Analysis on Abdominal Organs for Diabetes Prediction）</news:title>
   <news:publication_date>2026-06-02T11:09:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697025</loc>
  <lastmod>2026-06-02T11:08:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的多変量方策評価とBellman GANによる探索（DISTRIBUTIONAL MULTIVARIATE POLICY EVALUATION AND EXPLORATION WITH THE BELLMAN GAN）</news:title>
   <news:publication_date>2026-06-02T11:08:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697023</loc>
  <lastmod>2026-06-02T10:17:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V-FCNNによる心房の三次元自動セグメンテーション（V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation）</news:title>
   <news:publication_date>2026-06-02T10:17:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697021</loc>
  <lastmod>2026-06-02T10:17:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークフロー解析における外れ値検出（Outlier detection on network flow analysis）</news:title>
   <news:publication_date>2026-06-02T10:17:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697019</loc>
  <lastmod>2026-06-02T10:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤り訂正最大化に基づく深層画像ハッシュ法の設計（Error Correction Maximization for Deep Image Hashing）</news:title>
   <news:publication_date>2026-06-02T10:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697017</loc>
  <lastmod>2026-06-02T10:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>修正宇宙論におけるアクシオン・ミニクラスターの性質（Axion Miniclusters in Modified Cosmological Histories）</news:title>
   <news:publication_date>2026-06-02T10:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697015</loc>
  <lastmod>2026-06-02T10:16:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通制御のための効率的な深層強化学習モデル（An Efficient Deep Reinforcement Learning Model for Urban Traffic Control）</news:title>
   <news:publication_date>2026-06-02T10:16:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697013</loc>
  <lastmod>2026-06-02T10:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差メモリネットワーク：長期時系列依存を学習するフィードフォワード手法（Residual Memory Networks: Feed-forward approach to learn long temporal dependencies）</news:title>
   <news:publication_date>2026-06-02T10:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697011</loc>
  <lastmod>2026-06-02T10:16:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キーフレームベースの深層カメラ追跡と深度推定（DeepTAM: Deep Tracking and Mapping）</news:title>
   <news:publication_date>2026-06-02T10:16:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697008</loc>
  <lastmod>2026-06-02T09:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CANDELSz7：再電離期の銀河を狙った大規模分光観測（CANDELSz7: a large spectroscopic survey of CANDELS galaxies in the reionization epoch）</news:title>
   <news:publication_date>2026-06-02T09:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697006</loc>
  <lastmod>2026-06-02T09:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リバーシブルマルコフ連鎖における初期分布検定の統計的ウィンドウ（Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain）</news:title>
   <news:publication_date>2026-06-02T09:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697004</loc>
  <lastmod>2026-06-02T09:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識要約に基づく中国語判決文類似度の効率的手法（An Efficient Approach to Learning Chinese Judgment Document Similarity Based on Knowledge Summarization）</news:title>
   <news:publication_date>2026-06-02T09:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697002</loc>
  <lastmod>2026-06-02T09:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詳細な密な推論を可能にするウェーブレットCNN（Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform）</news:title>
   <news:publication_date>2026-06-02T09:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697000</loc>
  <lastmod>2026-06-02T09:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データストリームにおけるサブモジュラ最大化の越えられた壁（Beyond 0.5-Approximation for Submodular Maximization on Massive Data Streams）</news:title>
   <news:publication_date>2026-06-02T09:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696998</loc>
  <lastmod>2026-06-02T09:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽・動き・深度境界の推定を統合する汎用ネットワーク（Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation）</news:title>
   <news:publication_date>2026-06-02T09:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696996</loc>
  <lastmod>2026-06-02T09:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の物体のクラス獲得のための視覚的問い生成（Visual Question Generation for Class Acquisition of Unknown Objects）</news:title>
   <news:publication_date>2026-06-02T09:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696994</loc>
  <lastmod>2026-06-02T08:30:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Markov Chain Concentrationに基づく強化学習の後悔境界の刷新（Regret Bounds for Reinforcement Learning via Markov Chain Concentration）</news:title>
   <news:publication_date>2026-06-02T08:30:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696992</loc>
  <lastmod>2026-06-02T08:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術室映像の匿名化がもたらす現場とデータ利活用の転換（FaceOff: Anonymizing Videos in the Operating Rooms）</news:title>
   <news:publication_date>2026-06-02T08:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696990</loc>
  <lastmod>2026-06-02T08:30:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Saak変換による敵対的攻撃防御（Defense Against Adversarial Attacks with Saak Transform）</news:title>
   <news:publication_date>2026-06-02T08:30:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696988</loc>
  <lastmod>2026-06-02T08:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移の（U）LIRGsにおける塵に覆われた超新星の検出（Revealing Dusty Supernovae in High-Redshift (Ultra-)Luminous Infrared Galaxies through Near-Infrared Integrated Light Variability）</news:title>
   <news:publication_date>2026-06-02T08:29:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696986</loc>
  <lastmod>2026-06-02T08:29:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>kT因子分解におけるPgg TMD分裂関数（Pgg TMD splitting function in kT factorization）</news:title>
   <news:publication_date>2026-06-02T08:29:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696984</loc>
  <lastmod>2026-06-02T08:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化計算による深層畳み込みニューラルネットワークの最適化（On Optimizing Deep Convolutional Neural Networks by Evolutionary Computing）</news:title>
   <news:publication_date>2026-06-02T08:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696982</loc>
  <lastmod>2026-06-02T08:28:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ATLASによる全ハドロニック最終状態でのベクトル様（Vector-like）クォーク探索の要点（Search for pair production of heavy vector-like quarks decaying into hadronic final states in pp collisions at √s = 13 TeV with the ATLAS detector）</news:title>
   <news:publication_date>2026-06-02T08:28:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696980</loc>
  <lastmod>2026-06-02T07:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGに対する深層転移学習（DEEP TRANSFER LEARNING FOR EEG-BASED BRAIN COMPUTER INTERFACE）</news:title>
   <news:publication_date>2026-06-02T07:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696978</loc>
  <lastmod>2026-06-02T07:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グレイボックス敵対的学習（Gray-box Adversarial Training）</news:title>
   <news:publication_date>2026-06-02T07:37:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696976</loc>
  <lastmod>2026-06-02T07:37:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学における物理過程・現象の計算機シミュレーション学習法（Methods of Learning of Computer Simulation of Physical Processes and Phenomena in University）</news:title>
   <news:publication_date>2026-06-02T07:37:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696974</loc>
  <lastmod>2026-06-02T07:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NIMFA：非負値行列因子分解のためのPython統一ライブラリ（NIMFA : A Python Library for Nonnegative Matrix Factorization）</news:title>
   <news:publication_date>2026-06-02T07:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696972</loc>
  <lastmod>2026-06-02T07:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理教育におけるQRコード活用の可能性 (The Possibility of Use of QR-Codes in Teaching Physics)</news:title>
   <news:publication_date>2026-06-02T07:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696970</loc>
  <lastmod>2026-06-02T07:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的CVaRの収束境界（Concentration bounds for empirical conditional value-at-risk: The unbounded case）</news:title>
   <news:publication_date>2026-06-02T07:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696968</loc>
  <lastmod>2026-06-02T07:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による相転移の反復推定（Machine Learning Phase Transition: An Iterative Proposal）</news:title>
   <news:publication_date>2026-06-02T07:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696966</loc>
  <lastmod>2026-06-02T06:44:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし時空間特徴学習のスケーラビリティ組み込み（INCORPORATING SCALABILITY IN UNSUPERVISED SPATIO-TEMPORAL FEATURE LEARNING）</news:title>
   <news:publication_date>2026-06-02T06:44:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696964</loc>
  <lastmod>2026-06-02T06:44:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合コアアーキテクチャにおけるマルチスレッド負荷の省エネ予測（Energy-Efficiency Prediction of Multithreaded Workloads on Heterogeneous Composite Cores Architectures using Machine Learning Techniques）</news:title>
   <news:publication_date>2026-06-02T06:44:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696962</loc>
  <lastmod>2026-06-02T06:44:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>豊富な感覚入力による液体注ぎのモニタリング（Liquid Pouring Monitoring via Rich Sensory Inputs）</news:title>
   <news:publication_date>2026-06-02T06:44:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696960</loc>
  <lastmod>2026-06-02T06:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるバレンス力場モデル（Machine learning valence force field model）</news:title>
   <news:publication_date>2026-06-02T06:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696958</loc>
  <lastmod>2026-06-02T06:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチリード心電図の深層特徴融合による自動分類の実証（A Study of Deep Feature Fusion based Methods for Classifying Multi-lead ECG）</news:title>
   <news:publication_date>2026-06-02T06:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696956</loc>
  <lastmod>2026-06-02T06:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による分光計測の極度の簡素化（Machine Learning Promoting Extreme Simplification of Spectroscopy Equipment）</news:title>
   <news:publication_date>2026-06-02T06:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696954</loc>
  <lastmod>2026-06-02T06:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理知見を組み込んだニューラルネットワークによる原子スケール材料モデリング（Physically-informed artificial neural networks for atomistic modeling of materials）</news:title>
   <news:publication_date>2026-06-02T06:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696952</loc>
  <lastmod>2026-06-02T05:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド部分空間学習による高次元データ解析（Hybrid Subspace Learning for High-Dimensional Data）</news:title>
   <news:publication_date>2026-06-02T05:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696950</loc>
  <lastmod>2026-06-02T05:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度とロバスト性はトレードオフか（Is Robustness the Cost of Accuracy? – A Comprehensive Study on the Robustness of 18 Deep Image Classification Models）</news:title>
   <news:publication_date>2026-06-02T05:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696948</loc>
  <lastmod>2026-06-02T05:51:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肌病変診断のための大規模アンサンブルとスケールしないマルチクロップ評価（Skin Lesion Diagnosis using Ensembles, Unscaled Multi-Crop Evaluation and Loss Weighting）</news:title>
   <news:publication_date>2026-06-02T05:51:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696946</loc>
  <lastmod>2026-06-02T05:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D概念設計の深層学習による支援（3D CONCEPTUAL DESIGN USING DEEP LEARNING）</news:title>
   <news:publication_date>2026-06-02T05:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696944</loc>
  <lastmod>2026-06-02T05:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量データに対するセカントベースの階層的次元削減（Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets）</news:title>
   <news:publication_date>2026-06-02T05:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696942</loc>
  <lastmod>2026-06-02T05:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損値補完を深層生成モデルで考える（Missing Value Imputation Based on Deep Generative Models）</news:title>
   <news:publication_date>2026-06-02T05:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696940</loc>
  <lastmod>2026-06-02T05:49:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張畳み込みを用いた3D LGE-MRIにおける左心房セグメンテーション（Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRI）</news:title>
   <news:publication_date>2026-06-02T05:49:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696938</loc>
  <lastmod>2026-06-02T04:58:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチオブジェクティブ認知モデルによるfMRI分析の安定化（Multi-Objective Cognitive Model: a supervised approach for multi-subject fMRI analysis）</news:title>
   <news:publication_date>2026-06-02T04:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696936</loc>
  <lastmod>2026-06-02T04:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンシエーション（Instantiation）</news:title>
   <news:publication_date>2026-06-02T04:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696934</loc>
  <lastmod>2026-06-02T04:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化敵対的攻撃の実装と解釈性向上への挑戦 (STRUCTURED ADVERSARIAL ATTACK: TOWARDS GENERAL IMPLEMENTATION AND BETTER INTERPRETABILITY)</news:title>
   <news:publication_date>2026-06-02T04:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696932</loc>
  <lastmod>2026-06-02T04:49:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に専門家知識を埋め込むワイヤレスAI最適化（Model-Aided Wireless Artificial Intelligence: Embedding Expert Knowledge in Deep Neural Networks Towards Wireless Systems Optimization）</news:title>
   <news:publication_date>2026-06-02T04:49:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696930</loc>
  <lastmod>2026-06-02T04:48:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>依存関係グラフとCNNを組み合わせた回答トリガリング手法（Combining Graph-based Dependency Features with Convolutional Neural Network for Answer Triggering）</news:title>
   <news:publication_date>2026-06-02T04:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696928</loc>
  <lastmod>2026-06-02T04:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RR Tau（RR Tauri）の光度と分光学的挙動の再評価（Photometry and spectrophotometry of the Herbig Ae star RR Tauri）</news:title>
   <news:publication_date>2026-06-02T04:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696926</loc>
  <lastmod>2026-06-02T04:48:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Self-Attention Recurrent Networkによるサリエンシー検出の革新（Self-Attention Recurrent Network for Saliency Detection）</news:title>
   <news:publication_date>2026-06-02T04:48:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696924</loc>
  <lastmod>2026-06-02T03:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフィカルモデリングの視点から見た深層生成モデルの学習レビュー（A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling）</news:title>
   <news:publication_date>2026-06-02T03:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696922</loc>
  <lastmod>2026-06-02T03:56:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール監督ネットワークによる人体姿勢推定（MULTI-SCALE SUPERVISED NETWORK FOR HUMAN POSE ESTIMATION）</news:title>
   <news:publication_date>2026-06-02T03:56:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696920</loc>
  <lastmod>2026-06-02T03:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師ありセマンティックセグメンテーションのギャップを埋める方策（Towards Closing the Gap in Weakly Supervised Semantic Segmentation with DCNNs: Combining Local and Global Models）</news:title>
   <news:publication_date>2026-06-02T03:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696918</loc>
  <lastmod>2026-06-02T03:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動車ソフトウェアにおける機械学習の安全利用（Using Machine Learning Safely in Automotive Software）</news:title>
   <news:publication_date>2026-06-02T03:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696916</loc>
  <lastmod>2026-06-02T03:56:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スイッチングコストを考慮した無線スケジューリングにおける明示的学習を組み合わせたMax-Weight（Augmenting Max-Weight with Explicit Learning for Wireless Scheduling with Switching Costs）</news:title>
   <news:publication_date>2026-06-02T03:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696914</loc>
  <lastmod>2026-06-02T03:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚鏡画像の深層学習による分類（Classification of Dermoscopy Images using Deep Learning）</news:title>
   <news:publication_date>2026-06-02T03:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696912</loc>
  <lastmod>2026-06-02T03:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOC学習状況の時系列予測にLSTMを適用する意義（Predicting Learning Status in MOOCs using LSTM）</news:title>
   <news:publication_date>2026-06-02T03:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696910</loc>
  <lastmod>2026-06-02T03:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siciak極値関数と多項式の外部性に関する凸性の性質（Convexity properties related to extremal functions）</news:title>
   <news:publication_date>2026-06-02T03:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696908</loc>
  <lastmod>2026-06-02T03:04:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼からの深度推定を変える三眼仮定（Learning monocular depth estimation with unsupervised trinocular assumptions）</news:title>
   <news:publication_date>2026-06-02T03:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696906</loc>
  <lastmod>2026-06-02T03:03:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画素レベルセマンティクスによる画像色付け（Pixel-level Semantics Guided Image Colorization）</news:title>
   <news:publication_date>2026-06-02T03:03:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696904</loc>
  <lastmod>2026-06-02T03:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNの判断を解きほぐすLISA（LISA: Layer-wIse Semantic Accumulation and Example2Pattern）</news:title>
   <news:publication_date>2026-06-02T03:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696902</loc>
  <lastmod>2026-06-02T03:03:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己学習（Self-taught learning）のためのオートエンコーダに基づくサンプル選択（Autoencoder Based Sample Selection for Self-Taught Learning）</news:title>
   <news:publication_date>2026-06-02T03:03:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696900</loc>
  <lastmod>2026-06-02T03:03:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面調和関数残差ネットワークによる拡散信号のハーモナイゼーション（Spherical Harmonic Residual Network for Diffusion Signal Harmonization）</news:title>
   <news:publication_date>2026-06-02T03:03:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696898</loc>
  <lastmod>2026-06-02T03:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と言語の全局・局所対応による人物再識別の視覚表現改善（Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association）</news:title>
   <news:publication_date>2026-06-02T03:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696896</loc>
  <lastmod>2026-06-02T02:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ATMPAによる可視化ベースマルウェア検知への攻撃（ATMPA: Attacking Machine Learning-based Malware Visualization Detection Methods via Adversarial Examples）</news:title>
   <news:publication_date>2026-06-02T02:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696894</loc>
  <lastmod>2026-06-02T02:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価相関係数予測におけるARIMA-LSTMハイブリッド（Stock Price Correlation Coefficient Prediction with ARIMA-LSTM Hybrid Model）</news:title>
   <news:publication_date>2026-06-02T02:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696892</loc>
  <lastmod>2026-06-02T02:01:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tracklet Association Trackerによる多体追跡の統合的学習（Tracklet Association Tracker: An End-to-End Learning-based Association Approach for Multi-Object Tracking）</news:title>
   <news:publication_date>2026-06-02T02:01:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696890</loc>
  <lastmod>2026-06-02T02:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチセンター学習による顔アライメント（Deep Multi-Center Learning for Face Alignment）</news:title>
   <news:publication_date>2026-06-02T02:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696888</loc>
  <lastmod>2026-06-02T02:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>省エネ制約下での適応型ニューラルネットワーク設計（Designing Adaptive Neural Networks for Energy-Constrained Image Classification）</news:title>
   <news:publication_date>2026-06-02T02:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696886</loc>
  <lastmod>2026-06-02T02:00:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市間転移学習によるスマートシティ構築の加速（Smart City Development with Urban Transfer Learning）</news:title>
   <news:publication_date>2026-06-02T02:00:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696884</loc>
  <lastmod>2026-06-02T02:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D深さ方向デプスワイズ畳み込みによる3D視覚モデルの軽量化（3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks）</news:title>
   <news:publication_date>2026-06-02T02:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696882</loc>
  <lastmod>2026-06-02T01:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的入れ子基底に基づく多重スケールニューラルネットワーク (A multiscale neural network based on hierarchical nested bases)</news:title>
   <news:publication_date>2026-06-02T01:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696880</loc>
  <lastmod>2026-06-02T01:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたトリプレットネットワークによる話者ダイアリゼーション（Triplet Network with Attention for Speaker Diarization）</news:title>
   <news:publication_date>2026-06-02T01:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696878</loc>
  <lastmod>2026-06-02T01:09:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの平衡点への大域収束とVariational Inequalitiesの応用（Global Convergence to the Equilibrium of GANs using Variational Inequalities）</news:title>
   <news:publication_date>2026-06-02T01:09:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696876</loc>
  <lastmod>2026-06-02T01:08:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Reinforcement One-Shot Learningによる資源制約下のオンライン分類最適化（Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification Systems）</news:title>
   <news:publication_date>2026-06-02T01:08:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696874</loc>
  <lastmod>2026-06-02T01:08:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>12誘導心電図からの分離表現学習：心室頻拍起源の局在化への応用 (Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardia)</news:title>
   <news:publication_date>2026-06-02T01:08:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696872</loc>
  <lastmod>2026-06-02T01:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>侵襲的介入の中止は本当に寿命を短くするか（Withholding or withdrawing invasive interventions may not accelerate time to death among dying ICU patients）</news:title>
   <news:publication_date>2026-06-02T01:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696870</loc>
  <lastmod>2026-06-02T01:07:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面信号に対応したPyTorch拡張：DELIMITによる拡散イメージング向け深層学習（DELIMIT PyTorch - An extension for Deep Learning in Diffusion Imaging）</news:title>
   <news:publication_date>2026-06-02T01:07:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696868</loc>
  <lastmod>2026-06-02T00:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MCRM: Mother Compact Recurrent Memory（MCRM: Mother Compact Recurrent Memory）</news:title>
   <news:publication_date>2026-06-02T00:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696866</loc>
  <lastmod>2026-06-02T00:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界細胞による格子細胞の動的自己組織的誤差訂正（Dynamic self-organized error-correction of grid cells by border cells）</news:title>
   <news:publication_date>2026-06-02T00:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696864</loc>
  <lastmod>2026-06-02T00:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所強化エンコーダ・デコーダネットワークによる単一画像の雨滴除去（Non-locally Enhanced Encoder-Decoder Network for Single Image De-raining）</news:title>
   <news:publication_date>2026-06-02T00:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696862</loc>
  <lastmod>2026-06-02T00:15:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置情報だけで無線スケジューリングを学習する（Spatial Deep Learning for Wireless Scheduling）</news:title>
   <news:publication_date>2026-06-02T00:15:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696860</loc>
  <lastmod>2026-06-02T00:15:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる3Dデータ表現に対するディープラーニングの進展（A survey on Deep Learning Advances on Different 3D Data Representations）</news:title>
   <news:publication_date>2026-06-02T00:15:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696858</loc>
  <lastmod>2026-06-02T00:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Foregroundセグメンテーションの多重スケール特徴学習（Learning Multi-scale Features for Foreground Segmentation）</news:title>
   <news:publication_date>2026-06-02T00:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696856</loc>
  <lastmod>2026-06-02T00:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通解析への有界全変動デノイジングの応用 (Application of Bounded Total Variation Denoising in Urban Traffic Analysis)</news:title>
   <news:publication_date>2026-06-02T00:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696854</loc>
  <lastmod>2026-06-01T23:23:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像から実映像への変換による単一画像深度推定の実用化可能性（T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks）</news:title>
   <news:publication_date>2026-06-01T23:23:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696852</loc>
  <lastmod>2026-06-01T23:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗い位置合わせから学ぶ画像アライメント（Learning to Align Images using Weak Geometric Supervision）</news:title>
   <news:publication_date>2026-06-01T23:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696850</loc>
  <lastmod>2026-06-01T23:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル数学環境としてのSageの実用性（Web-based Mobile Mathematical Environments with Sage）</news:title>
   <news:publication_date>2026-06-01T23:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696848</loc>
  <lastmod>2026-06-01T23:22:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造認識型形状テンプレートを用いた幾何学の解析 (Parsing Geometry Using Structure-Aware Shape Templates)</news:title>
   <news:publication_date>2026-06-01T23:22:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696846</loc>
  <lastmod>2026-06-01T23:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズネットワーク学習における多目的最適化の性能検証（Investigating the performance of multi-objective optimization when learning Bayesian Networks）</news:title>
   <news:publication_date>2026-06-01T23:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696844</loc>
  <lastmod>2026-06-01T23:21:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活動銀河核のブラックホールと銀河のスケーリング関係（BLACK HOLE - GALAXY SCALING RELATIONSHIPS FOR ACTIVE GALACTIC NUCLEI WITH REVERBERATION MASSES）</news:title>
   <news:publication_date>2026-06-01T23:21:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696842</loc>
  <lastmod>2026-06-01T23:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>純粋に幾何学的な3Dシーンの対応と検索（Purely Geometric Scene Association and Retrieval）</news:title>
   <news:publication_date>2026-06-01T23:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696840</loc>
  <lastmod>2026-06-01T22:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補完的正則化の力：変換学習と低ランクモデリングによる画像復元（The Power of Complementary Regularizers: Image Recovery via Transform Learning and Low-Rank Modeling）</news:title>
   <news:publication_date>2026-06-01T22:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696838</loc>
  <lastmod>2026-06-01T22:19:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統合型深層学習ネットワークによる新しいトポロジ設計アプローチ（A NOVEL TOPOLOGY DESIGN APPROACH USING AN INTEGRATED DEEP LEARNING NETWORK ARCHITECTURE）</news:title>
   <news:publication_date>2026-06-01T22:19:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696836</loc>
  <lastmod>2026-06-01T22:19:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長持ちする構造：蛾の嗅覚ネットワークにおける機能的・構造的機構が神経損傷の影響を緩和する（Built to Last: Functional and structural mechanisms in the moth olfactory network mitigate effects of neural injury）</news:title>
   <news:publication_date>2026-06-01T22:19:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696834</loc>
  <lastmod>2026-06-01T22:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク理論に基づくターゲティングは技術普及を促進するか（Can Network Theory-based Targeting Increase Technology Adoption?）</news:title>
   <news:publication_date>2026-06-01T22:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696832</loc>
  <lastmod>2026-06-01T22:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光フォトニック・インメモリで実現するスパイキングニューラルネットワーク（A Photonic In-Memory Computing primitive for Spiking Neural Networks using Phase-Change Materials）</news:title>
   <news:publication_date>2026-06-01T22:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696830</loc>
  <lastmod>2026-06-01T22:18:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチホップ特徴変調による視覚的推論（Visual Reasoning with Multi-hop Feature Modulation）</news:title>
   <news:publication_date>2026-06-01T22:18:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696828</loc>
  <lastmod>2026-06-01T22:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情・センチメント・強度を同時予測するマルチタスク・アンサンブルフレームワーク (A Multi-task Ensemble Framework for Emotion, Sentiment and Intensity Prediction)</news:title>
   <news:publication_date>2026-06-01T22:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696826</loc>
  <lastmod>2026-06-01T21:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブラーニングによるAndroid再パッケージ化マルウェアの刺激と検出（Stimulation and Detection of Android Repackaged Malware with Active Learning）</news:title>
   <news:publication_date>2026-06-01T21:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696824</loc>
  <lastmod>2026-06-01T21:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化データ上の過剰パラメータ化ニューラルネットワークの学習（Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data）</news:title>
   <news:publication_date>2026-06-01T21:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696822</loc>
  <lastmod>2026-06-01T21:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習における不確実性推定が変える多発性硬化症病変検出（Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation）</news:title>
   <news:publication_date>2026-06-01T21:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696820</loc>
  <lastmod>2026-06-01T21:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いた静的マルウェア解析の調査とチュートリアル（Machine Learning Aided Static Malware Analysis: A Survey and Tutorial）</news:title>
   <news:publication_date>2026-06-01T21:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696818</loc>
  <lastmod>2026-06-01T21:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト・スペクトル・フィルタリングと異常検知 (Robust Spectral Filtering and Anomaly Detection)</news:title>
   <news:publication_date>2026-06-01T21:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696816</loc>
  <lastmod>2026-06-01T21:16:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習モデルの信頼性を検証する―デジタル鑑識の事例研究（Enabling Trust in Deep Learning Models: A Digital Forensics Case Study）</news:title>
   <news:publication_date>2026-06-01T21:16:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696814</loc>
  <lastmod>2026-06-01T21:16:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース制御のための構造化ニューラルネットワークダイナミクス（Structured Neural Network Dynamics for Model-based Control）</news:title>
   <news:publication_date>2026-06-01T21:16:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696812</loc>
  <lastmod>2026-06-01T20:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース記事の内容駆動型無監督クラスタリング（Content-driven, unsupervised clustering of news articles through multiscale graph partitioning）</news:title>
   <news:publication_date>2026-06-01T20:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696810</loc>
  <lastmod>2026-06-01T20:25:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習における一般化誤差（Generalization Error in Deep Learning）</news:title>
   <news:publication_date>2026-06-01T20:25:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696808</loc>
  <lastmod>2026-06-01T20:24:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバー脅威インテリジェンスの挑戦と機会（Cyberthreat Intelligence: Challenges and Opportunities）</news:title>
   <news:publication_date>2026-06-01T20:24:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696806</loc>
  <lastmod>2026-06-01T20:23:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力線モデムによるケーブル診断とスマートグリッド監視（Cable Diagnostics with Power Line Modems for Smart Grid Monitoring）</news:title>
   <news:publication_date>2026-06-01T20:23:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696804</loc>
  <lastmod>2026-06-01T20:23:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子群最適化における2次元学習フレームワークによる特徴選択（A Two-Dimensional (2-D) Learning Framework for Particle Swarm based Feature Selection）</news:title>
   <news:publication_date>2026-06-01T20:23:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696802</loc>
  <lastmod>2026-06-01T20:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hoeffding木のnmin適応による省エネ化（Hoeffding Trees with nmin adaptation）</news:title>
   <news:publication_date>2026-06-01T20:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696800</loc>
  <lastmod>2026-06-01T20:23:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ無しで普遍的敵対的摂動を作る方法（Ask, Acquire, and Attack: Data-free UAP Generation using Class Impressions）</news:title>
   <news:publication_date>2026-06-01T20:23:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696798</loc>
  <lastmod>2026-06-01T19:31:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的潜在相互作用を持つマルチタスクガウス過程（Multitask Gaussian Process with Hierarchical Latent Interactions）</news:title>
   <news:publication_date>2026-06-01T19:31:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696796</loc>
  <lastmod>2026-06-01T19:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの精密3D姿勢推定を繰り返し精緻化するiSPA-Net（iSPA-Net : Iterative Semantic Pose Alignment Network）</news:title>
   <news:publication_date>2026-06-01T19:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696794</loc>
  <lastmod>2026-06-01T19:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間飛行計測による散乱光トモグラフィーの計算的復元（Computational time-of-flight diffuse optical tomography）</news:title>
   <news:publication_date>2026-06-01T19:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696792</loc>
  <lastmod>2026-06-01T19:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的分布表現によるマルチショット人物再識別（Multi-shot Person Re-identification through Set Distance with Visual Distributional Representation）</news:title>
   <news:publication_date>2026-06-01T19:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696790</loc>
  <lastmod>2026-06-01T19:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加法ベイズネットワークの情報理論的スコア学習（Information-Theoretic Scoring Rules to Learn Additive Bayesian Network Applied to Epidemiology）</news:title>
   <news:publication_date>2026-06-01T19:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696788</loc>
  <lastmod>2026-06-01T19:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PHI Scrubber: 医療テキストから個人識別情報を取り除く深層学習アプローチ（PHI Scrubber: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-06-01T19:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696786</loc>
  <lastmod>2026-06-01T19:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル極値と共分散埋め込みによる効率的なテクスチャ検索（Efficient texture retrieval using multiscale local extrema descriptors and covariance embedding）</news:title>
   <news:publication_date>2026-06-01T19:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696784</loc>
  <lastmod>2026-06-01T18:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子閉じ込めを含む超薄型ジャンクションレス二重ゲートFETの電荷ベースモデル (Charge-based Model for Ultra-Thin Junctionless DG FETs, Including Quantum Confinement)</news:title>
   <news:publication_date>2026-06-01T18:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696782</loc>
  <lastmod>2026-06-01T18:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Interaction-aware Spatio-temporal Pyramid Attentionによる行動分類の革新（Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification）</news:title>
   <news:publication_date>2026-06-01T18:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696780</loc>
  <lastmod>2026-06-01T18:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良型Deep Spectral Convolutionによるハイパースペクトル混合分解（Improved Deep Spectral Convolution Network For Hyperspectral Unmixing With Multinomial Mixture Kernel and Endmember Uncertainty）</news:title>
   <news:publication_date>2026-06-01T18:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696778</loc>
  <lastmod>2026-06-01T18:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメインに依存しない画像を「幻視」して汎用化する手法（Hallucinating Agnostic Images to Generalize Across Domains）</news:title>
   <news:publication_date>2026-06-01T18:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696776</loc>
  <lastmod>2026-06-01T18:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像→映像検索の高速化のための局所インデックス化と深層特徴信頼度の活用（Exploiting Local Indexing and Deep Feature Confidence Scores for Fast Image-to-Video Search）</news:title>
   <news:publication_date>2026-06-01T18:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696774</loc>
  <lastmod>2026-06-01T18:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Code Shrewによるプログラミング教育の再設計（Code Shrew: Software platform for teaching programming through drawings and animations）</news:title>
   <news:publication_date>2026-06-01T18:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696772</loc>
  <lastmod>2026-06-01T18:35:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CurriculumNetによる大規模ウェブ画像からの弱教師あり学習（CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images）</news:title>
   <news:publication_date>2026-06-01T18:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696770</loc>
  <lastmod>2026-06-01T17:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HELIXによる反復的機械学習の高速化（HELIX: Accelerating Human-in-the-loop Machine Learning）</news:title>
   <news:publication_date>2026-06-01T17:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696768</loc>
  <lastmod>2026-06-01T17:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートグリッドにおける深層学習による誤データ注入検出（Dynamic Detection of False Data Injection Attack in Smart Grid using Deep Learning）</news:title>
   <news:publication_date>2026-06-01T17:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696766</loc>
  <lastmod>2026-06-01T17:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的トピック関係を正則化するテンソル分解による専門家推薦（Expert Recommendation via Tensor Factorization with Regularizing Hierarchical Topical Relationships）</news:title>
   <news:publication_date>2026-06-01T17:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696764</loc>
  <lastmod>2026-06-01T17:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画から人物を再特定する新しい視点：Deep Siamese Attention Networks（Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-06-01T17:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696762</loc>
  <lastmod>2026-06-01T17:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ依存の自動管理による再現性向上（DataDeps.jl: Repeatable Data Setup for Replicable Data Science）</news:title>
   <news:publication_date>2026-06-01T17:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696760</loc>
  <lastmod>2026-06-01T17:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歴史と現在から学ぶ次のアイテム推薦（Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors）</news:title>
   <news:publication_date>2026-06-01T17:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696758</loc>
  <lastmod>2026-06-01T17:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転不変性を持つギア連結CNNの提案（Geared Rotationally Identical and Invariant Convolutional Neural Network Systems）</news:title>
   <news:publication_date>2026-06-01T17:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696756</loc>
  <lastmod>2026-06-01T16:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密集群衆のカウント・密度推定・局所化の合成損失（Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds）</news:title>
   <news:publication_date>2026-06-01T16:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696754</loc>
  <lastmod>2026-06-01T16:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強健回帰による自動融合プラズマ解析（Robust Regression for Automatic Fusion Plasma Analysis based on Generative Modeling）</news:title>
   <news:publication_date>2026-06-01T16:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696752</loc>
  <lastmod>2026-06-01T16:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Information Bottleneck on Vector Quantized Autoencoders（Variational Information Bottleneck on Vector Quantized Autoencoders）</news:title>
   <news:publication_date>2026-06-01T16:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696750</loc>
  <lastmod>2026-06-01T16:49:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>上空画像から何が見えるかを予測する（WHAT GOES WHERE: PREDICTING OBJECT DISTRIBUTIONS FROM ABOVE）</news:title>
   <news:publication_date>2026-06-01T16:49:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696748</loc>
  <lastmod>2026-06-01T16:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クリエイティブな可視化機会ワークショップの枠組み（A Framework for Creative Visualization-Opportunities Workshops）</news:title>
   <news:publication_date>2026-06-01T16:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696746</loc>
  <lastmod>2026-06-01T16:48:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック2D材料における切替可能な一方向プラズモニックビーコン（Switchable and unidirectional plasmonic beacons in hyperbolic 2D materials）</news:title>
   <news:publication_date>2026-06-01T16:48:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696744</loc>
  <lastmod>2026-06-01T16:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型ローカル制御による配電網の最適化（Data-driven Local Control Design for Active Distribution Grids using off-line Optimal Power Flow and Machine Learning Techniques）</news:title>
   <news:publication_date>2026-06-01T16:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696742</loc>
  <lastmod>2026-06-01T15:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低輝度AGNとX線連星の人口研究が示す新しい視点（LOW-LUMINOSITY AGN AND X-RAY BINARY POPULATIONS IN COSMOS STAR-FORMING GALAXIES）</news:title>
   <news:publication_date>2026-06-01T15:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696740</loc>
  <lastmod>2026-06-01T15:57:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良された交差エントロピー推定器を用いる尤度フリー推論（Likelihood-free inference with an improved cross-entropy estimator）</news:title>
   <news:publication_date>2026-06-01T15:57:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696738</loc>
  <lastmod>2026-06-01T15:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハドロン対と単一ハドロンの背中合わせ準包摂生成（Semi-inclusive back-to-back production of a hadron pair and a single hadron in e+e− annihilation）</news:title>
   <news:publication_date>2026-06-01T15:56:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696736</loc>
  <lastmod>2026-06-01T15:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型非滑らか最適化の学習的アプローチ（Data-driven Nonsmooth Optimization）</news:title>
   <news:publication_date>2026-06-01T15:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696734</loc>
  <lastmod>2026-06-01T15:55:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Streaming Kernel PCAの高速化と省メモリ化（Streaming Kernel PCA with ˜O(√n) Random Features）</news:title>
   <news:publication_date>2026-06-01T15:55:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696732</loc>
  <lastmod>2026-06-01T15:55:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆多目的最適化によるパラメータ推定（Inferring Parameters Through Inverse Multiobjective Optimization）</news:title>
   <news:publication_date>2026-06-01T15:55:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696730</loc>
  <lastmod>2026-06-01T15:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離表現による多様な画像間変換（Diverse Image-to-Image Translation via Disentangled Representations）</news:title>
   <news:publication_date>2026-06-01T15:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696728</loc>
  <lastmod>2026-06-01T15:03:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間分数微分方程式の機械学習による発見（MACHINE LEARNING OF SPACE-FRACTIONAL DIFFERENTIAL EQUATIONS）</news:title>
   <news:publication_date>2026-06-01T15:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
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