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   <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>
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   <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>
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   <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>
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   <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>
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   <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>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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   <news:title>Saak変換による敵対的攻撃防御（Defense Against Adversarial Attacks with Saak Transform）</news:title>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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   <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>
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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>EEGに対する深層転移学習（DEEP TRANSFER LEARNING FOR EEG-BASED BRAIN COMPUTER INTERFACE）</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>グレイボックス敵対的学習（Gray-box Adversarial Training）</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>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>
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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>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>
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   <news:genres>Blog</news:genres>
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   <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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>経験的CVaRの収束境界（Concentration bounds for empirical conditional value-at-risk: The unbounded case）</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>機械学習による相転移の反復推定（Machine Learning Phase Transition: An Iterative Proposal）</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>
   </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>
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   <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>
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   <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>
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  <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>
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  <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>
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  <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>
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  <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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696726</loc>
  <lastmod>2026-06-01T14:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚観察から学ぶ行動可能な表現（Learning Actionable Representations from Visual Observations）</news:title>
   <news:publication_date>2026-06-01T14:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696724</loc>
  <lastmod>2026-06-01T14:51:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバーブリング検出の技術報告（Cyberbullying Detection – Technical Report 2/2018）</news:title>
   <news:publication_date>2026-06-01T14:51:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696722</loc>
  <lastmod>2026-06-01T14:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T14:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696720</loc>
  <lastmod>2026-06-01T14:51:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャネル変分オートエンコーダによる半盲目的音源分離（SEMI-BLIND SOURCE SEPARATION WITH MULTICHANNEL VARIATIONAL AUTOENCODER）</news:title>
   <news:publication_date>2026-06-01T14:51:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696718</loc>
  <lastmod>2026-06-01T14:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子-光子の深窓: ホログラフィックQCDにおける小x振る舞いの解明（Electron-photon deep inelastic scattering at small x in holographic QCD）</news:title>
   <news:publication_date>2026-06-01T14:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696716</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lyapunovニューラルネットワークによる安全学習の保証（The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems）</news:title>
   <news:publication_date>2026-06-01T14:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696714</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T13:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696712</loc>
  <lastmod>2026-06-01T13:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T13:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696710</loc>
  <lastmod>2026-06-01T13:57:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テニス動作認識を変える「履歴を持つLSTM」の提案（RGB Video Based Tennis Action Recognition Using a Deep Historical Long Short-Term Memory）</news:title>
   <news:publication_date>2026-06-01T13:57:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696708</loc>
  <lastmod>2026-06-01T13:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消失（Erasures）下のノイジーブロードキャスト問題の新展開（Algorithms for Noisy Broadcast under Erasures）</news:title>
   <news:publication_date>2026-06-01T13:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696706</loc>
  <lastmod>2026-06-01T13:56:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T13:56:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696704</loc>
  <lastmod>2026-06-01T13:56:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696702</loc>
  <lastmod>2026-06-01T13:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T13:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696700</loc>
  <lastmod>2026-06-01T13:04:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒストグラム変換に基づく話者識別の実践的理解（Histogram Transform-based Speaker Identification）</news:title>
   <news:publication_date>2026-06-01T13:04:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696698</loc>
  <lastmod>2026-06-01T12:54:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEG信号の分類における非ガウス中立ベクトルの応用 (Classification of EEG Signal based on non-Gaussian Neutral Vector)</news:title>
   <news:publication_date>2026-06-01T12:54:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696696</loc>
  <lastmod>2026-06-01T12:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNAメチル化データ解析のための深層ニューラルネットワーク（Deep Neural Network for Analysis of DNA Methylation Data）</news:title>
   <news:publication_date>2026-06-01T12:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696694</loc>
  <lastmod>2026-06-01T12:53:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トリプルカチオン・ハイブリッドペロブスカイトにおける静的・動的無秩序の役割（Static and Dynamic Disorder in Triple-Cation Hybrid Perovskites）</news:title>
   <news:publication_date>2026-06-01T12:53:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696692</loc>
  <lastmod>2026-06-01T12:52:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な活性化関数の探求（The Quest for the Golden Activation Function）</news:title>
   <news:publication_date>2026-06-01T12:52:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696690</loc>
  <lastmod>2026-06-01T12:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T12:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696688</loc>
  <lastmod>2026-06-01T12:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル大規模データ解析と機械学習の展開（Mobile big data analysis with machine learning）</news:title>
   <news:publication_date>2026-06-01T12:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696686</loc>
  <lastmod>2026-06-01T12:00:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-01T12:00:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-01T12:00:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層特徴集合の頑健な注意集約によるマルチビュー3D再構成（Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction）</news:title>
   <news:publication_date>2026-06-01T12:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696680</loc>
  <lastmod>2026-06-01T11:59:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層自己教師付き輪郭埋め込みニューラルネットワークによる肝臓セグメンテーション（Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation）</news:title>
   <news:publication_date>2026-06-01T11:59:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696678</loc>
  <lastmod>2026-06-01T11:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度を用いた無界損失のオンライン集合学習（Online Aggregation of Unbounded Losses Using Shifting Experts with Confidence）</news:title>
   <news:publication_date>2026-06-01T11:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696676</loc>
  <lastmod>2026-06-01T11:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイナリ重みを用いたメモリスティブなアナログ深層ニューラルネットワーク（Binary Weighted Memristive Analog Deep Neural Network for Near-Sensor Edge Processing）</news:title>
   <news:publication_date>2026-06-01T11:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696674</loc>
  <lastmod>2026-06-01T11:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常視覚ドメインへの動的適応（Dynamic Adaptation on Non-Stationary Visual Domains）</news:title>
   <news:publication_date>2026-06-01T11:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696672</loc>
  <lastmod>2026-06-01T11:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元回帰の実務的比較（High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking）</news:title>
   <news:publication_date>2026-06-01T11:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696670</loc>
  <lastmod>2026-06-01T11:05:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RecoGym: オンライン広告の推薦問題のための強化学習環境（RecoGym: A Reinforcement Learning Environment for the Problem of Product Recommendation in Online Advertising）</news:title>
   <news:publication_date>2026-06-01T11:05:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696668</loc>
  <lastmod>2026-06-01T11:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホリスティック情報を用いたトリガー設計がもたらす実務的インパクト（Using holistic event information in the trigger）</news:title>
   <news:publication_date>2026-06-01T11:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696666</loc>
  <lastmod>2026-06-01T11:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ配置の可読性を画像から評価する深層学習手法（Evaluating the Readability of Force Directed Graph Layouts: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-06-01T11:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696664</loc>
  <lastmod>2026-06-01T11:04:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルセンサを用いたゼロショット姿勢分類における属性の重要度（Attributes’ Importance for Zero-Shot Pose-Classification Based on Wearable Sensors）</news:title>
   <news:publication_date>2026-06-01T11:04:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696662</loc>
  <lastmod>2026-06-01T11:03:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成がレコメンドと出会う：グループ向け新規アイテム提案の研究（Generation Meets Recommendation: Proposing Novel Items for Groups of Users）</news:title>
   <news:publication_date>2026-06-01T11:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696660</loc>
  <lastmod>2026-06-01T11:03:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響シーン分類コンペティションの総括（ACOUSTIC SCENE CLASSIFICATION: A COMPETITION REVIEW）</news:title>
   <news:publication_date>2026-06-01T11:03:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696658</loc>
  <lastmod>2026-06-01T10:11:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群の形状補完を行うPoint Completion Network（Point Completion Network）</news:title>
   <news:publication_date>2026-06-01T10:11:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696656</loc>
  <lastmod>2026-06-01T10:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識における言語探索最適化（Linguistic Search Optimization for Deep Learning Based LVCSR）</news:title>
   <news:publication_date>2026-06-01T10:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696654</loc>
  <lastmod>2026-06-01T10:11:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元非線形混合におけるブラインドソース分離の実現可能性（On the achievability of blind source separation for high-dimensional nonlinear source mixtures）</news:title>
   <news:publication_date>2026-06-01T10:11:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696652</loc>
  <lastmod>2026-06-01T10:10:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス識別的学習による音響キーワード検出の改良（Sequence Discriminative Training for Deep Learning based Acoustic Keyword Spotting）</news:title>
   <news:publication_date>2026-06-01T10:10:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696650</loc>
  <lastmod>2026-06-01T10:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチセルネットワークにおける無線資源配分を深層学習で解く（Deep Learning for Radio Resource Allocation in Multi-Cell Networks）</news:title>
   <news:publication_date>2026-06-01T10:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696648</loc>
  <lastmod>2026-06-01T10:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピッチアクセント注釈の誤りがニューラル音声合成に与える影響（Investigating accuracy of pitch-accent annotations in neural network-based speech synthesis and denoising effects）</news:title>
   <news:publication_date>2026-06-01T10:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696646</loc>
  <lastmod>2026-06-01T10:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動ベースの暗黙認証における動的多層特権制御（Dynamic Multi-level Privilege Control in Behavior-based Implicit Authentication Systems Leveraging Mobile Devices）</news:title>
   <news:publication_date>2026-06-01T10:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696644</loc>
  <lastmod>2026-06-01T09:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子共鳴がもたらす減衰増強 — プラズマフォトニック結晶における実験的検証（Enhanced Attenuation Arising from Lattice Resonances in a Plasma Photonic Crystal）</news:title>
   <news:publication_date>2026-06-01T09:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696642</loc>
  <lastmod>2026-06-01T09:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LIMEで局所説明を得て規則化する：LIME-FOLDによる非単調論理プログラム帰納（Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME）</news:title>
   <news:publication_date>2026-06-01T09:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696640</loc>
  <lastmod>2026-06-01T09:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フュージョンによる部分空間クラスタリング（Fusion Subspace Clustering: Full &amp;amp; Incomplete Data）</news:title>
   <news:publication_date>2026-06-01T09:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696638</loc>
  <lastmod>2026-06-01T09:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニバーサル・ユニタリ光デバイスの行列最適化（Matrix optimization on universal unitary photonic devices）</news:title>
   <news:publication_date>2026-06-01T09:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696636</loc>
  <lastmod>2026-06-01T09:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合行列補完の概念と実用性（Mixture Matrix Completion）</news:title>
   <news:publication_date>2026-06-01T09:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696634</loc>
  <lastmod>2026-06-01T09:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>科学可視化の「記憶されやすさ」を深く探る（Toward A Deep Understanding of What Makes a Scientific Visualization Memorable）</news:title>
   <news:publication_date>2026-06-01T09:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696632</loc>
  <lastmod>2026-06-01T09:09:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次ボルツァノフィルタのための再帰的Geman-McClure推定器（Recursive Geman-McClure Estimator for Implementing Second-Order Volterra Filter）</news:title>
   <news:publication_date>2026-06-01T09:09:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696630</loc>
  <lastmod>2026-06-01T08:17:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理モデル制約GANによる画像復元とその拡張（Physics-Based Generative Adversarial Models for Image Restoration and Beyond）</news:title>
   <news:publication_date>2026-06-01T08:17:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696628</loc>
  <lastmod>2026-06-01T08:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIM図面を深層学習で分類する（Classification of Building Information Model (BIM) Structures with Deep Learning）</news:title>
   <news:publication_date>2026-06-01T08:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696626</loc>
  <lastmod>2026-06-01T08:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLCapsuleによるオフラインで守られたML提供（MLCapsule: Guarded Offline Deployment of Machine Learning as a Service）</news:title>
   <news:publication_date>2026-06-01T08:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696624</loc>
  <lastmod>2026-06-01T08:16:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>包摂的DISにおけるトランスバースィティ性と新しいTMD和則（Transversity in inclusive DIS and novel TMD sum rules）</news:title>
   <news:publication_date>2026-06-01T08:16:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696622</loc>
  <lastmod>2026-06-01T08:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BICEP Arrayのクライオスタットとマウント設計（BICEP Array cryostat and mount design）</news:title>
   <news:publication_date>2026-06-01T08:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696620</loc>
  <lastmod>2026-06-01T08:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データ下での森構造学習と普遍符号化（Forest Learning from Data and its Universal Coding）</news:title>
   <news:publication_date>2026-06-01T08:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696618</loc>
  <lastmod>2026-06-01T08:15:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>紫外線における銀河構造の波長依存性（Galaxy Structure in the Ultraviolet: The Dependence of Morphological Parameters on Rest-Frame Wavelength）</news:title>
   <news:publication_date>2026-06-01T08:15:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696616</loc>
  <lastmod>2026-06-01T07:23:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮可能なスペクトル混合カーネルと疎な依存構造によるガウス過程の改良（Compressible Spectral Mixture Kernels with Sparse Dependency Structures for Gaussian Processes）</news:title>
   <news:publication_date>2026-06-01T07:23:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696614</loc>
  <lastmod>2026-06-01T07:23:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生干渉下での堅牢なキーワードスポッティングのためのデータ拡張（Data Augmentation for Robust Keyword Spotting Under Playback Interference）</news:title>
   <news:publication_date>2026-06-01T07:23:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696612</loc>
  <lastmod>2026-06-01T07:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の傾きで変わる星形成指標の見え方（OMEGA – OSIRIS Mapping of Emission-line Galaxies in A901/2: IV. – Extinction of Star-Formation Estimators with Inclination）</news:title>
   <news:publication_date>2026-06-01T07:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696610</loc>
  <lastmod>2026-06-01T07:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信ネットワークの同質性を用いたユーザ人口統計属性の推定（Inference of Users Demographic Attributes based on Homophily in Communication Networks）</news:title>
   <news:publication_date>2026-06-01T07:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696608</loc>
  <lastmod>2026-06-01T07:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調群最適化とアリコロニーの学習混合が示す実務的含意（Cooperative Group Optimization with Ants (CGO-AS): Leverage Optimization with Mixed Individual and Social Learning）</news:title>
   <news:publication_date>2026-06-01T07:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696606</loc>
  <lastmod>2026-06-01T07:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mod-DeepESN：モジュラ型ディープ・エコー・ステート・ネットワーク（Mod-DeepESN: Modular Deep Echo State Network）</news:title>
   <news:publication_date>2026-06-01T07:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696604</loc>
  <lastmod>2026-06-01T07:21:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知カテゴリ検知とPAC保証（Open Category Detection with PAC Guarantees）</news:title>
   <news:publication_date>2026-06-01T07:21:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696602</loc>
  <lastmod>2026-06-01T06:30:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元車両操舵予測の学習フレームワーク（A Learning-based Framework for Two-Dimensional Vehicle Maneuver Prediction Over V2V Networks）</news:title>
   <news:publication_date>2026-06-01T06:30:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696600</loc>
  <lastmod>2026-06-01T06:30:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル算術論理ユニット（Neural Arithmetic Logic Units）</news:title>
   <news:publication_date>2026-06-01T06:30:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696598</loc>
  <lastmod>2026-06-01T06:30:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SlimNets: 深層モデルの圧縮と高速化の探究 (SlimNets: An Exploration of Deep Model Compression and Acceleration)</news:title>
   <news:publication_date>2026-06-01T06:30:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696596</loc>
  <lastmod>2026-06-01T06:29:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群の意味的分類を変える近傍定義（Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods）</news:title>
   <news:publication_date>2026-06-01T06:29:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696594</loc>
  <lastmod>2026-06-01T06:29:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークにおける分散深層強化学習による動的送信電力制御（Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks）</news:title>
   <news:publication_date>2026-06-01T06:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696592</loc>
  <lastmod>2026-06-01T06:29:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真空誘起CP破れが生む複素CKM行列と制御されたスカラーFCNC（Vacuum Induced CP Violation Generating a Complex CKM Matrix with Controlled Scalar FCNC）</news:title>
   <news:publication_date>2026-06-01T06:29:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696590</loc>
  <lastmod>2026-06-01T06:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低遅延ニューラル音声翻訳の実装と応用（Low-Latency Neural Speech Translation）</news:title>
   <news:publication_date>2026-06-01T06:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696588</loc>
  <lastmod>2026-06-01T05:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子量子物質イメージング実験における機械学習（Machine Learning in Electronic Quantum Matter Imaging Experiments）</news:title>
   <news:publication_date>2026-06-01T05:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696586</loc>
  <lastmod>2026-06-01T05:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形ポテンシャルによる多体系の局在化 — ブロッホ振動から多体局在化へ（From Bloch Oscillations to Many Body Localization in Clean Interacting Systems）</news:title>
   <news:publication_date>2026-06-01T05:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696584</loc>
  <lastmod>2026-06-01T05:37:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画のフリッカーを“見えないまま”安定化する手法（Learning Blind Video Temporal Consistency）</news:title>
   <news:publication_date>2026-06-01T05:37:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696582</loc>
  <lastmod>2026-06-01T05:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生核ヒルベルト空間による行列補完と外挿（Matrix completion and extrapolation via kernel regression）</news:title>
   <news:publication_date>2026-06-01T05:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696580</loc>
  <lastmod>2026-06-01T05:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実地で見つけるAndroidステゴアプリ対策（Tackling Android Stego Apps in the Wild）</news:title>
   <news:publication_date>2026-06-01T05:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696578</loc>
  <lastmod>2026-06-01T05:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Seqとマルチタスク学習によるドメイン特化型インタプリタの共同意図・内容抽出（Seq2Seq and Multi-Task Learning for joint intent and content extraction for domain specific interpreters）</news:title>
   <news:publication_date>2026-06-01T05:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696576</loc>
  <lastmod>2026-06-01T05:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価チャートパターン認識と深層学習（Stock Chart Pattern recognition with Deep Learning）</news:title>
   <news:publication_date>2026-06-01T05:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696574</loc>
  <lastmod>2026-06-01T04:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な漸進的ニューラルアーキテクチャ探索（Efficient Progressive Neural Architecture Search）</news:title>
   <news:publication_date>2026-06-01T04:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696572</loc>
  <lastmod>2026-06-01T04:44:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの難易度がアノテーターのラベリング精度に与える影響（How Does Tweet Difficulty Affect Labeling Performance of Annotators?）</news:title>
   <news:publication_date>2026-06-01T04:44:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696570</loc>
  <lastmod>2026-06-01T04:43:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの最適化可能性とエネルギー地形の幾何学（Geometry of energy landscapes and the optimizability of deep neural networks）</news:title>
   <news:publication_date>2026-06-01T04:43:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696568</loc>
  <lastmod>2026-06-01T04:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の高忠実表示を実現する深層外観モデル（Deep Appearance Models for Face Rendering）</news:title>
   <news:publication_date>2026-06-01T04:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696566</loc>
  <lastmod>2026-06-01T04:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者の進行方向推定に基づく自動車用MIMOレーダー解析（Pedestrian Motion Direction Estimation Using Simulated Automotive MIMO Radar）</news:title>
   <news:publication_date>2026-06-01T04:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696564</loc>
  <lastmod>2026-06-01T04:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル『リドルレス』回帰でも一般化する理由（Just Interpolate: Kernel Ridgeless Regression Can Generalize）</news:title>
   <news:publication_date>2026-06-01T04:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696562</loc>
  <lastmod>2026-06-01T04:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー対応カーネル二標本検定（A Differentially Private Kernel Two-Sample Test）</news:title>
   <news:publication_date>2026-06-01T04:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696560</loc>
  <lastmod>2026-06-01T03:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化微分学習による閾値自動設定（Structured Differential Learning for Automatic Threshold Setting）</news:title>
   <news:publication_date>2026-06-01T03:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696558</loc>
  <lastmod>2026-06-01T03:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ごちゃごちゃ環境から汎化可能なロボット技能を学ぶ（Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments）</news:title>
   <news:publication_date>2026-06-01T03:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696556</loc>
  <lastmod>2026-06-01T03:51:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メール通知における情報開示の好みと懸念の研究（Studying Preferences and Concerns about Information Disclosure in Email Notifications）</news:title>
   <news:publication_date>2026-06-01T03:51:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696554</loc>
  <lastmod>2026-06-01T03:50:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的形状モデルにおけるモデル次数選択（Model-Order Selection in Statistical Shape Models）</news:title>
   <news:publication_date>2026-06-01T03:50:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696552</loc>
  <lastmod>2026-06-01T03:50:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの俯瞰図生成（Generative Adversarial Frontal View to Bird View Synthesis）</news:title>
   <news:publication_date>2026-06-01T03:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696550</loc>
  <lastmod>2026-06-01T03:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混同誤りを明示的に削減するネットワーク構造（A Network Structure to Explicitly Reduce Confusion Errors in Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-01T03:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696548</loc>
  <lastmod>2026-06-01T03:49:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>de Sitter時空の赤外量子ゆらぎに対する安定性（Stability of de Sitter spacetime against infrared quantum scalar field fluctuations）</news:title>
   <news:publication_date>2026-06-01T03:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696546</loc>
  <lastmod>2026-06-01T02:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ランダム主観的期待効用（Dynamic Random Subjective Expected Utility）</news:title>
   <news:publication_date>2026-06-01T02:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696544</loc>
  <lastmod>2026-06-01T02:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードアテンションによる視覚質問応答の効率化（Learning Visual Question Answering by Bootstrapping Hard Attention）</news:title>
   <news:publication_date>2026-06-01T02:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696542</loc>
  <lastmod>2026-06-01T02:58:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミューオンニュートリノの荷電流深部非弾性散乱と鉄核の効果（Charged current deep inelastic scattering of νµ off 56Fe）</news:title>
   <news:publication_date>2026-06-01T02:58:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696540</loc>
  <lastmod>2026-06-01T02:57:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNのマルチGPUにおけるエネルギーベースのチューニング（Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs）</news:title>
   <news:publication_date>2026-06-01T02:57:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696538</loc>
  <lastmod>2026-06-01T02:57:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境情報学における自然計算の応用レビュー（A Review on the Application of Natural Computing in Environmental Informatics）</news:title>
   <news:publication_date>2026-06-01T02:57:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696536</loc>
  <lastmod>2026-06-01T02:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度マップを用いたドローン検出（Drone Detection Using Depth Maps）</news:title>
   <news:publication_date>2026-06-01T02:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696534</loc>
  <lastmod>2026-06-01T02:56:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なVQA：注意機構の自動監督による視覚的グラウンディング（Interpretable Visual Question Answering by Visual Grounding from Attention Supervision Mining）</news:title>
   <news:publication_date>2026-06-01T02:56:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696532</loc>
  <lastmod>2026-06-01T02:05:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダで学ぶ瞬時数認識（Subitizing with Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-01T02:05:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696530</loc>
  <lastmod>2026-06-01T02:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情評価の深層ニューラルモデル（A Deep Neural Model Of Emotion Appraisal）</news:title>
   <news:publication_date>2026-06-01T02:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696528</loc>
  <lastmod>2026-06-01T02:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリレベルの6自由度物体姿勢推定（Category-level 6D Object Pose Recovery in Depth Images）</news:title>
   <news:publication_date>2026-06-01T02:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696526</loc>
  <lastmod>2026-06-01T02:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続的探索を伴う学習戦略に対するRobbins–Monro条件の整理（Robbins-Monro Conditions for Persistent Exploration Learning Strategies）</news:title>
   <news:publication_date>2026-06-01T02:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696524</loc>
  <lastmod>2026-06-01T02:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索品質をユーザー行動から予測する手法の実務的意義（Did We Get It Right? Predicting Query Performance in E-commerce Search）</news:title>
   <news:publication_date>2026-06-01T02:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696522</loc>
  <lastmod>2026-06-01T02:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳放射線手術向け腫瘍輪郭抽出のConvNetと非均一パッチ生成（Tumor Delineation For Brain Radiosurgery by a ConvNet and Non-Uniform Patch Generation）</news:title>
   <news:publication_date>2026-06-01T02:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696520</loc>
  <lastmod>2026-06-01T02:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフポリシー評価とログ化バンディット学習における誤差低減（Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy）</news:title>
   <news:publication_date>2026-06-01T02:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696518</loc>
  <lastmod>2026-06-01T01:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験・模倣・熟考：孔子の学びと機械学習（Experience, Imitation and Reflection; Confucius’ Conjecture and Machine Learning）</news:title>
   <news:publication_date>2026-06-01T01:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696516</loc>
  <lastmod>2026-06-01T01:11:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークを時相オートマトンで定式化しパラメータ学習を行う手法（Spiking Neural Networks modelled as Timed Automata with parameter learning）</news:title>
   <news:publication_date>2026-06-01T01:11:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696514</loc>
  <lastmod>2026-06-01T01:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィッシャー情報近似による最小記述長に基づくモデル選択（Model selection by minimum description length: Lower-bound sample sizes for the Fisher information approximation）</news:title>
   <news:publication_date>2026-06-01T01:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696512</loc>
  <lastmod>2026-06-01T01:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPU上での効率的推論のためのバイナリ化畳み込みニューラルネットワーク（Binarized Convolutional Neural Networks for Efficient Inference on GPUs）</news:title>
   <news:publication_date>2026-06-01T01:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696510</loc>
  <lastmod>2026-06-01T01:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小尤度に基づくGANによる異常検知（Anomaly Detection via Minimum Likelihood Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-01T01:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696508</loc>
  <lastmod>2026-06-01T01:10:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロ選手の自転車データに基づく機械学習の試み（TOWARDS MACHINE LEARNING ON DATA FROM PROFESSIONAL CYCLISTS）</news:title>
   <news:publication_date>2026-06-01T01:10:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696506</loc>
  <lastmod>2026-06-01T01:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MaxMin Linear による Fuzzy C-Means 初期化法の実務的含意（MaxMin Linear Initialization for Fuzzy C-Means）</news:title>
   <news:publication_date>2026-06-01T01:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696503</loc>
  <lastmod>2026-06-01T00:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manifold: モデル非依存の可視化による機械学習モデル診断フレームワーク（Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models）</news:title>
   <news:publication_date>2026-06-01T00:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696501</loc>
  <lastmod>2026-06-01T00:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化と強化学習を統合したニューラルアーキテクチャ探索（RENAS: Reinforced Evolutionary Neural Architecture Search）</news:title>
   <news:publication_date>2026-06-01T00:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696499</loc>
  <lastmod>2026-06-01T00:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph R-CNNによるシーングラフ生成（Graph R-CNN for Scene Graph Generation）</news:title>
   <news:publication_date>2026-06-01T00:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696497</loc>
  <lastmod>2026-06-01T00:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一言語と多言語のゼロショット文体変換（Monolingual and Cross-lingual Zero-shot Style Transfer）</news:title>
   <news:publication_date>2026-06-01T00:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696495</loc>
  <lastmod>2026-06-01T00:16:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サムネイルから要約へ：単一の深層ニューラルネットワークによる映像要約の統一的手法（FROM THUMBNAILS TO SUMMARIES - A SINGLE DEEP NEURAL NETWORK TO RULE THEM ALL）</news:title>
   <news:publication_date>2026-06-01T00:16:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696493</loc>
  <lastmod>2026-06-01T00:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体非依存の視覚関係特徴を学ぶShuffle-Then-Assemble（Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features）</news:title>
   <news:publication_date>2026-06-01T00:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696491</loc>
  <lastmod>2026-06-01T00:15:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巧緻なハンド内操作の学習（Learning Dexterous In-Hand Manipulation）</news:title>
   <news:publication_date>2026-06-01T00:15:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696489</loc>
  <lastmod>2026-05-31T23:24:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの深度推定を変えた学習型アフィニティ伝搬（Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network）</news:title>
   <news:publication_date>2026-05-31T23:24:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696487</loc>
  <lastmod>2026-05-31T23:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次世代の動画内広告自動差し替えシステム（An Advert Creation System for Next-Gen Publicity）</news:title>
   <news:publication_date>2026-05-31T23:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696485</loc>
  <lastmod>2026-05-31T23:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス単位の人間パースを一括で解く仕組み（Instance-level Human Parsing via Part Grouping Network）</news:title>
   <news:publication_date>2026-05-31T23:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696483</loc>
  <lastmod>2026-05-31T23:23:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングベースのベイズ強化学習による推定と制御（Estimation and Control Using Sampling-Based Bayesian Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-31T23:23:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696481</loc>
  <lastmod>2026-05-31T23:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心拍変動をCNNで定量化して覚醒/睡眠を分類する手法（SLEEP-WAKE CLASSIFICATION VIA QUANTIFYING HEART RATE VARIABILITY BY CONVOLUTIONAL NEURAL NETWORK）</news:title>
   <news:publication_date>2026-05-31T23:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696479</loc>
  <lastmod>2026-05-31T23:23:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二分評価の理論と変数選択への応用 (A Theory of Dichotomous Valuation with Applications to Variable Selection)</news:title>
   <news:publication_date>2026-05-31T23:23:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696477</loc>
  <lastmod>2026-05-31T23:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルなサイクル一貫性を用いた汎化ゼロショット学習（Multi-modal Cycle-consistent Generalized Zero-Shot Learning）</news:title>
   <news:publication_date>2026-05-31T23:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696475</loc>
  <lastmod>2026-05-31T22:31:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知的手法によるサイバー攻撃の早期検知（Cognitive Techniques for Early Detection of Cybersecurity Events）</news:title>
   <news:publication_date>2026-05-31T22:31:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696473</loc>
  <lastmod>2026-05-31T22:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空中で指を書くログイン方式の提案（FMCode: A 3D In-the-Air Finger Motion Based User Login Framework for Gesture Interface）</news:title>
   <news:publication_date>2026-05-31T22:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696471</loc>
  <lastmod>2026-05-31T22:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃に依存しない敵対的入力の防御（EagleEye: Attack-Agnostic Defense against Adversarial Inputs）</news:title>
   <news:publication_date>2026-05-31T22:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696469</loc>
  <lastmod>2026-05-31T22:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パルスシーケンスに強い高速脳セグメンテーション（Pulse Sequence Resilient Fast Brain Segmentation）</news:title>
   <news:publication_date>2026-05-31T22:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696467</loc>
  <lastmod>2026-05-31T22:30:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所化信頼度を獲得することで物体検出の精度を高める（Acquisition of Localization Confidence for Accurate Object Detection）</news:title>
   <news:publication_date>2026-05-31T22:30:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696465</loc>
  <lastmod>2026-05-31T22:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テザン5における遷移型ミリ秒パルサ候補の発見（THE MAVERIC SURVEY: A TRANSITIONAL MILLISECOND PULSAR CANDIDATE IN TERZAN 5）</news:title>
   <news:publication_date>2026-05-31T22:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696463</loc>
  <lastmod>2026-05-31T22:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嗜好同定の限界と実験デザイン（Preference Identification）</news:title>
   <news:publication_date>2026-05-31T22:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696461</loc>
  <lastmod>2026-05-31T21:38:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トレーニング初期に画像を小さくすることで学習効率を上げる手法（Testing the ‘Efficient Network TRaining (ENTR)’ Hypothesis）</news:title>
   <news:publication_date>2026-05-31T21:38:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696459</loc>
  <lastmod>2026-05-31T21:38:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図ノイズ除去のための深い再帰的デノイジングニューラルネットワーク（Deep Recurrent Denoising Neural Network）</news:title>
   <news:publication_date>2026-05-31T21:38:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696457</loc>
  <lastmod>2026-05-31T21:38:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み合わせ学習によるシステムプログラミング教育の設計（Design of Blended Learning of System Programming for Bachelors of Software Engineering）</news:title>
   <news:publication_date>2026-05-31T21:38:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696455</loc>
  <lastmod>2026-05-31T21:37:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Call Detail Recordsを用いた異常検知とトラフィック予測（Call Detail Records Driven Anomaly Detection and Traffic Prediction in Mobile Cellular Networks）</news:title>
   <news:publication_date>2026-05-31T21:37:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696453</loc>
  <lastmod>2026-05-31T21:37:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転におけるテキスト説明の作り方（Textual Explanations for Self-Driving Vehicles）</news:title>
   <news:publication_date>2026-05-31T21:37:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696451</loc>
  <lastmod>2026-05-31T21:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マーカー不要の視覚的ロボット学習（Markerless Visual Robot Programming by Demonstration）</news:title>
   <news:publication_date>2026-05-31T21:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696449</loc>
  <lastmod>2026-05-31T21:36:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低xにおける偏極スピン1/2ハドロンからの深部非弾性散乱（Deep inelastic scattering from polarized spin-1/2 hadrons at low x from string theory）</news:title>
   <news:publication_date>2026-05-31T21:36:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696447</loc>
  <lastmod>2026-05-31T20:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合体銀河団CIZA J2242.8+5301の深部VLA観測（Deep Very Large Array Observations of the Merging Cluster CIZA J2242.8+5301）</news:title>
   <news:publication_date>2026-05-31T20:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696445</loc>
  <lastmod>2026-05-31T20:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脆性材料の破壊推定をグラフ理論で行う（Estimating Failure in Brittle Materials using Graph Theory）</news:title>
   <news:publication_date>2026-05-31T20:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696443</loc>
  <lastmod>2026-05-31T20:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アベル1795中心部における複数回AGN活動の痕跡（Signatures of multiple episodes of AGN activity in the core of Abell 1795）</news:title>
   <news:publication_date>2026-05-31T20:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696441</loc>
  <lastmod>2026-05-31T20:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二ハドロン相関を使ったクォークヘリシティの可視化（Accessing quark helicity in e+e− and SIDIS via dihadron correlations）</news:title>
   <news:publication_date>2026-05-31T20:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696439</loc>
  <lastmod>2026-05-31T20:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少データ学習で転移を変える学習率の妙（Improving Transferability of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-31T20:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696437</loc>
  <lastmod>2026-05-31T20:43:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御可能な音声合成のための深いエンコーダ・デコーダモデル（Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis）</news:title>
   <news:publication_date>2026-05-31T20:43:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696435</loc>
  <lastmod>2026-05-31T20:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団の星間光は暗黒物質の分布を示すか（Intracluster light: a luminous tracer for dark matter in clusters of galaxies）</news:title>
   <news:publication_date>2026-05-31T20:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696433</loc>
  <lastmod>2026-05-31T19:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実世界の低解像度顔画像を超解像するために劣化過程を学ばせる（To learn image super-resolution, use a GAN to learn how to do image degradation first）</news:title>
   <news:publication_date>2026-05-31T19:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696431</loc>
  <lastmod>2026-05-31T19:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的PET画像のファクター解析：ガウスノイズを越えて（Factor analysis of dynamic PET images: beyond Gaussian noise）</news:title>
   <news:publication_date>2026-05-31T19:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696429</loc>
  <lastmod>2026-05-31T19:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要求トレーサビリティ自動化：KDDから学んだ20年（Automating Requirements Traceability: Two Decades of Learning from KDD）</news:title>
   <news:publication_date>2026-05-31T19:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696427</loc>
  <lastmod>2026-05-31T19:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像の動き情報を使って人のセグメンテーションを改善する手法（Leveraging Motion Priors in Videos for Improving Human Segmentation）</news:title>
   <news:publication_date>2026-05-31T19:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696425</loc>
  <lastmod>2026-05-31T19:50:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルマンフィルタに基づくヒューリスティックアンサンブル（Kalman Filter-based Heuristic Ensemble）</news:title>
   <news:publication_date>2026-05-31T19:50:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696423</loc>
  <lastmod>2026-05-31T19:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼底画像における視神経乳頭とカップの深層分割（Deep Optic Disc and Cup Segmentation in Fundus Images Using U-Net and Multi-scale Feature Matching Networks）</news:title>
   <news:publication_date>2026-05-31T19:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696421</loc>
  <lastmod>2026-05-31T19:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパレータ・ネットワーク（Comparator Networks）</news:title>
   <news:publication_date>2026-05-31T19:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696419</loc>
  <lastmod>2026-05-31T18:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元推定とsum-of-squares証明（High-dimensional estimation via sum-of-squares proofs）</news:title>
   <news:publication_date>2026-05-31T18:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696417</loc>
  <lastmod>2026-05-31T18:58:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な特徴学習と任意サイズ画像のステガノ解析（Efficient feature learning and multi-size image steganalysis based on CNN）</news:title>
   <news:publication_date>2026-05-31T18:58:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696415</loc>
  <lastmod>2026-05-31T18:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNの収束と汎化を加速する一般化最適更新（Faster Convergence &amp;amp; Generalization in DNNs）</news:title>
   <news:publication_date>2026-05-31T18:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696413</loc>
  <lastmod>2026-05-31T18:57:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリー理論は本当に必要か（WHO NEEDS CATEGORY THEORY?）</news:title>
   <news:publication_date>2026-05-31T18:57:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696411</loc>
  <lastmod>2026-05-31T18:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所線形フォレストが変える回帰の精度と解釈性（Local Linear Forests）</news:title>
   <news:publication_date>2026-05-31T18:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696409</loc>
  <lastmod>2026-05-31T18:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HybridNet: 分類と再構成の協調による半教師あり学習（HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-05-31T18:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696407</loc>
  <lastmod>2026-05-31T18:57:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師あり学習と線形逆問題の接続（ON THE CONNECTION BETWEEN SUPERVISED LEARNING AND LINEAR INVERSE PROBLEMS）</news:title>
   <news:publication_date>2026-05-31T18:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696405</loc>
  <lastmod>2026-05-31T18:05:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス不均衡に強い分類器チェーンの作り方（Making Classifier Chains Resilient to Class Imbalance）</news:title>
   <news:publication_date>2026-05-31T18:05:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696403</loc>
  <lastmod>2026-05-31T17:55:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選好（ペア比較）に基づくオンライン学習とデュエリングバンディット（Preference-based Online Learning with Dueling Bandits: A Survey）</news:title>
   <news:publication_date>2026-05-31T17:55:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696401</loc>
  <lastmod>2026-05-31T17:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速画像復元のための多区間学習可能線形ユニット（Multi-bin Trainable Linear Unit for Fast Image Restoration Networks）</news:title>
   <news:publication_date>2026-05-31T17:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696399</loc>
  <lastmod>2026-05-31T17:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>著者名同定における不均衡学習データの影響（The impact of imbalanced training data on machine learning for author name disambiguation）</news:title>
   <news:publication_date>2026-05-31T17:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696397</loc>
  <lastmod>2026-05-31T17:54:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dropout-GAN：動的識別器アンサンブルから学ぶ生成（Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators）</news:title>
   <news:publication_date>2026-05-31T17:54:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696395</loc>
  <lastmod>2026-05-31T17:54:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的一貫性を保つ空間特徴選択による適応判別相関フィルタ学習（Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection）</news:title>
   <news:publication_date>2026-05-31T17:54:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696393</loc>
  <lastmod>2026-05-31T17:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全身MRIにおける微小臓器セグメンテーションの改善――二段階FCNと重み付けスキームの応用（Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes）</news:title>
   <news:publication_date>2026-05-31T17:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696391</loc>
  <lastmod>2026-05-31T17:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットカー視点からの行動検出（Action Detection from a Robot-Car Perspective）</news:title>
   <news:publication_date>2026-05-31T17:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696389</loc>
  <lastmod>2026-05-31T17:01:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル密度推定に基づく隠れ状態付きマルコフモデル（Kernel Density Estimation-Based Markov Models with Hidden State）</news:title>
   <news:publication_date>2026-05-31T17:01:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696387</loc>
  <lastmod>2026-05-31T17:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークと位相回復によるハーモニック・パーカッシブ音源分離（HARMONIC-PERCUSSIVE SOURCE SEPARATION WITH DEEP NEURAL NETWORKS AND PHASE RECOVERY）</news:title>
   <news:publication_date>2026-05-31T17:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696385</loc>
  <lastmod>2026-05-31T17:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習による教師なしドメイン適応で堅牢な音声認識を実現する（Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition）</news:title>
   <news:publication_date>2026-05-31T17:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696383</loc>
  <lastmod>2026-05-31T17:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視聴コンテキストが変えるTVレコメンドの精度と多様性（The Importance of Context When Recommending TV Content: Dataset and Algorithms）</news:title>
   <news:publication_date>2026-05-31T17:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696381</loc>
  <lastmod>2026-05-31T17:00:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再現核ヒルベルト空間における確率的方策勾配上昇（Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces）</news:title>
   <news:publication_date>2026-05-31T17:00:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696379</loc>
  <lastmod>2026-05-31T17:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間的自己教師あり学習を深層強化学習で改善する（Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-31T17:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696377</loc>
  <lastmod>2026-05-31T16:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNベース表面予測における不確実性の定量化（Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors）</news:title>
   <news:publication_date>2026-05-31T16:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696375</loc>
  <lastmod>2026-05-31T16:08:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィルタグループ近似による極端なネットワーク圧縮（Extreme Network Compression via Filter Group Approximation）</news:title>
   <news:publication_date>2026-05-31T16:08:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696373</loc>
  <lastmod>2026-05-31T16:08:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高移動環境での迅速なアナログ伝送がエッジ学習を変える（Fast Analog Transmission for High-Mobility Wireless Data Acquisition in Edge Learning）</news:title>
   <news:publication_date>2026-05-31T16:08:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696371</loc>
  <lastmod>2026-05-31T16:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空中画像のマルチラベル分類におけるクラス毎注意を再帰的に探るネットワーク（Recurrently Exploring Class-wise Attention in A Hybrid Convolutional and Bidirectional LSTM Network for Multi-label Aerial Image Classification）</news:title>
   <news:publication_date>2026-05-31T16:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696369</loc>
  <lastmod>2026-05-31T16:07:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール式センサ融合によるセマンティックセグメンテーション（Modular Sensor Fusion for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-31T16:07:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696367</loc>
  <lastmod>2026-05-31T16:06:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的ニューラル機械翻訳へのアクティブラーニング適用（Active Learning for Interactive Neural Machine Translation of Data Streams）</news:title>
   <news:publication_date>2026-05-31T16:06:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696365</loc>
  <lastmod>2026-05-31T16:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に高分解能画像におけるセマンティックラベリングの自己カスケード畳み込みネットワーク（Semantic Labeling in Very High Resolution Images via A Self-Cascaded Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-31T16:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696363</loc>
  <lastmod>2026-05-31T15:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情表現を3次元で圧縮する手法 CAKE（CAKE: Compact and Accurate K-dimensional representation of Emotion）</news:title>
   <news:publication_date>2026-05-31T15:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696361</loc>
  <lastmod>2026-05-31T15:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド実写・合成データ学習による内在分解（Deep Hybrid Real and Synthetic Training for Intrinsic Decomposition）</news:title>
   <news:publication_date>2026-05-31T15:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696359</loc>
  <lastmod>2026-05-31T15:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽度認知障害からアルツハイマー病への進行予測と神経画像の影響（Predicting Conversion of Mild Cognitive Impairments to Alzheimer’s Disease and Exploring Impact of Neuroimaging）</news:title>
   <news:publication_date>2026-05-31T15:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696357</loc>
  <lastmod>2026-05-31T15:05:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人再識別のためのハード認識点対集合ディープメトリック（Hard-Aware Point-to-Set Deep Metric for Person Re-identification）</news:title>
   <news:publication_date>2026-05-31T15:05:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696355</loc>
  <lastmod>2026-05-31T15:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ねじれた単環中空フォトニッククリスタルファイバーにおける強い円二色性（Strong circular dichroism in twisted single-ring hollow-core photonic crystal fiber）</news:title>
   <news:publication_date>2026-05-31T15:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696353</loc>
  <lastmod>2026-05-31T15:05:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合精度による超高速深層学習トレーニング（Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes）</news:title>
   <news:publication_date>2026-05-31T15:05:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696351</loc>
  <lastmod>2026-05-31T15:04:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 5018群における銀河構造と群間光のマッピング（VEGAS: A VST Early-type GAlaxy Survey. III. Mapping the galaxy structure, interactions and intragroup light in the NGC 5018 group）</news:title>
   <news:publication_date>2026-05-31T15:04:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696349</loc>
  <lastmod>2026-05-31T14:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画認識を高速化する軽量化アーキテクチャの提案（Multi-Fiber Networks for Video Recognition）</news:title>
   <news:publication_date>2026-05-31T14:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696347</loc>
  <lastmod>2026-05-31T14:12:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リファクタリング向け自動クローン推薦の現在と過去に基づく手法（Automatic Clone Recommendation for Refactoring Based on the Present and the Past）</news:title>
   <news:publication_date>2026-05-31T14:12:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696345</loc>
  <lastmod>2026-05-31T14:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>End-to-End Deep Kronecker-Product Matching を用いた人再識別の革新（End-to-End Deep Kronecker-Product Matching for Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-05-31T14:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696343</loc>
  <lastmod>2026-05-31T14:11:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的物体認識によるモバイルロボットの探索戦略（Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots）</news:title>
   <news:publication_date>2026-05-31T14:11:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696341</loc>
  <lastmod>2026-05-31T14:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Human Motion Analysis with Deep Metric Learning（Human Motion Analysis with Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-31T14:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696339</loc>
  <lastmod>2026-05-31T14:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための深層グループシャッフルランダムウォーク（Deep Group-shuffling Random Walk for Person Re-identification）</news:title>
   <news:publication_date>2026-05-31T14:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696337</loc>
  <lastmod>2026-05-31T14:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>月の位相教育における仮想現実の有用性（Virtual Reality as a Teaching Tool for Moon Phases and Beyond）</news:title>
   <news:publication_date>2026-05-31T14:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696335</loc>
  <lastmod>2026-05-31T13:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換に不変な畳み込みニューラルネットワークの構築法（Transformationally Identical and Invariant CNNs by Combining Symmetric Operations or Input Vectors）</news:title>
   <news:publication_date>2026-05-31T13:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696333</loc>
  <lastmod>2026-05-31T13:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼ完璧な専門家によるオンライン学習（Online Learning with an Almost Perfect Expert）</news:title>
   <news:publication_date>2026-05-31T13:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696331</loc>
  <lastmod>2026-05-31T13:10:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算抽象に対する群論的アプローチ（A Group-Theoretic Approach to Computational Abstraction）</news:title>
   <news:publication_date>2026-05-31T13:10:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696329</loc>
  <lastmod>2026-05-31T13:09:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習中の割り込みを学ぶ（Learning to Interrupt: A Hierarchical Deep Reinforcement Learning Framework for Efficient Exploration）</news:title>
   <news:publication_date>2026-05-31T13:09:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696327</loc>
  <lastmod>2026-05-31T13:08:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な生徒ネットワーク学習（Robust Student Network Learning）</news:title>
   <news:publication_date>2026-05-31T13:08:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696325</loc>
  <lastmod>2026-05-31T12:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損関節の復元による3D人体姿勢推定の改善（Occluded Joints Recovery in 3D Human Pose Estimation based on Distance Matrix）</news:title>
   <news:publication_date>2026-05-31T12:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696323</loc>
  <lastmod>2026-05-31T12:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量試料で39Ar年代測定を可能にし海洋換気を明らかにする（39Ar dating with small samples resolves ocean ventilation）</news:title>
   <news:publication_date>2026-05-31T12:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696321</loc>
  <lastmod>2026-05-31T12:16:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PMCとPadé法によるpQCD予測力の拡張（Extending the Predictive Power of Perturbative QCD）</news:title>
   <news:publication_date>2026-05-31T12:16:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696319</loc>
  <lastmod>2026-05-31T12:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク完遂型対話システムの挑戦（Microsoft Dialogue Challenge: Building End-to-End Task-Completion Dialogue Systems）</news:title>
   <news:publication_date>2026-05-31T12:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696317</loc>
  <lastmod>2026-05-31T12:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルメッシュ：空間とエネルギー保存の概念を導入する試み（Neural Mesh: Introducing a Notion of Space and Conservation of Energy to Neural Nets）</news:title>
   <news:publication_date>2026-05-31T12:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696315</loc>
  <lastmod>2026-05-31T12:15:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ARMによる離散潜在変数モデルの勾配推定法（AUGMENT-REINFORCE-MERGE GRADIENT FOR STOCHASTIC BINARY NETWORKS）</news:title>
   <news:publication_date>2026-05-31T12:15:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696313</loc>
  <lastmod>2026-05-31T12:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>旋律スタイルに基づく音声セグメンテーション（Audio segmentation based on melodic style with hand-crafted features and with convolutional neural networks）</news:title>
   <news:publication_date>2026-05-31T12:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696311</loc>
  <lastmod>2026-05-31T11:24:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド指向の学習ツールシステム（THE SYSTEM OF CLOUD ORIENTED LEARNING TOOLS AS AN ELEMENT OF EDUCATIONAL AND SCIENTIFIC ENVIRONMENT OF HIGH SCHOOL）</news:title>
   <news:publication_date>2026-05-31T11:24:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696309</loc>
  <lastmod>2026-05-31T11:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Reinforced Auto-Zoom Netによる乳がん全スライド画像分割の高速化と高精度化（Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images）</news:title>
   <news:publication_date>2026-05-31T11:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696307</loc>
  <lastmod>2026-05-31T11:23:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ROP攻撃検出に深層学習を組み合わせる新潮流（ROPNN: Using Deep Neural Networks to Accurately Detect ROP Payloads）</news:title>
   <news:publication_date>2026-05-31T11:23:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696305</loc>
  <lastmod>2026-05-31T11:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニコチン性アセチルコリン受容体の境界脂質と自発的分離の可視化（Boundary lipids of the nicotinic acetylcholine receptor: spontaneous partitioning via coarse-grained molecular dynamics simulation）</news:title>
   <news:publication_date>2026-05-31T11:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696303</loc>
  <lastmod>2026-05-31T11:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生の音声信号から位置を直接推定する終端型音響定位（Towards End-to-End Acoustic Localization using Deep Learning: from Audio Signal to Source Position Coordinates）</news:title>
   <news:publication_date>2026-05-31T11:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696301</loc>
  <lastmod>2026-05-31T11:22:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声生成に向けたリアルタイムMRIからの声識別（Towards Automatic Speech Identification from Vocal Tract Shape Dynamics in Real-time MRI）</news:title>
   <news:publication_date>2026-05-31T11:22:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696299</loc>
  <lastmod>2026-05-31T11:21:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StructADMMによる構造化重み剪定の実務的意義（StructADMM: A Systematic, High-Efficiency Framework of Structured Weight Pruning for DNNs）</news:title>
   <news:publication_date>2026-05-31T11:21:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696297</loc>
  <lastmod>2026-05-31T10:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療記録における関係分類の統合モデル（Convolutional Gated Recurrent Units for Medical Relation Classification）</news:title>
   <news:publication_date>2026-05-31T10:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696295</loc>
  <lastmod>2026-05-31T10:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の再演学習：境界転送によるReenactGAN（ReenactGAN: Learning to Reenact Faces via Boundary Transfer）</news:title>
   <news:publication_date>2026-05-31T10:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696293</loc>
  <lastmod>2026-05-31T10:20:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成雨と実世界雨のギャップを埋める半教師あり転移学習（Semi-supervised Transfer Learning for Image Rain Removal）</news:title>
   <news:publication_date>2026-05-31T10:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696291</loc>
  <lastmod>2026-05-31T10:19:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>挑戦に対するマインドセットの適用可能性を探る（Exploring Mindset’s Applicability to Students’ Experiences with Challenge in Transformed College Physics Courses）</news:title>
   <news:publication_date>2026-05-31T10:19:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696289</loc>
  <lastmod>2026-05-31T10:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関フィルタ追跡のための表現と切断推論の共同学習 (Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking)</news:title>
   <news:publication_date>2026-05-31T10:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696287</loc>
  <lastmod>2026-05-31T10:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形からの話者認識を変えるSincNet（SPEAKER RECOGNITION FROM RAW WAVEFORM WITH SINCNET）</news:title>
   <news:publication_date>2026-05-31T10:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696285</loc>
  <lastmod>2026-05-31T10:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariゲーム間の視覚的類推による強化学習における転移学習の研究（Visual Analogies between Atari Games for Studying Transfer Learning in RL）</news:title>
   <news:publication_date>2026-05-31T10:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696283</loc>
  <lastmod>2026-05-31T09:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>節のvivification（Clause Vivification by Unit Propagation in CDCL SAT Solvers）</news:title>
   <news:publication_date>2026-05-31T09:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696281</loc>
  <lastmod>2026-05-31T09:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNを用いた人物再識別で成果を出す3つの良い実践（Three Good Practices for Building Effective CNN Baseline Model for Person Re-identification）</news:title>
   <news:publication_date>2026-05-31T09:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696279</loc>
  <lastmod>2026-05-31T09:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における効率的な不確かさ推定（Efficient Uncertainty Estimation for Semantic Segmentation in Videos）</news:title>
   <news:publication_date>2026-05-31T09:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696277</loc>
  <lastmod>2026-05-31T09:25:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜カラー眼底画像における緑内障評価のためのマルチタスク深層学習（A Deep Learning based Joint Segmentation and Classiﬁcation Framework for Glaucoma Assesment in Retinal Color Fundus Images）</news:title>
   <news:publication_date>2026-05-31T09:25:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696275</loc>
  <lastmod>2026-05-31T09:25:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MoCoNet: 3D MPRAGE画像の運動補正をCNNで行う手法（MoCoNet: Motion Correction in 3D MPRAGE images using a Convolutional Neural Network approach）</news:title>
   <news:publication_date>2026-05-31T09:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696273</loc>
  <lastmod>2026-05-31T09:25:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テクスチャ混合を再定義する：深層統計をガウスモデルで補間する手法（Texture Mixing by Interpolating Deep Statistics via Gaussian Models）</news:title>
   <news:publication_date>2026-05-31T09:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696271</loc>
  <lastmod>2026-05-31T09:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitzグラフオンに対する多項式時間の非シード付きグラフマッチングの一貫的手法（Consistent polynomial-time unseeded graph matching for Lipschitz graphons）</news:title>
   <news:publication_date>2026-05-31T09:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696269</loc>
  <lastmod>2026-05-31T08:33:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tiny-DSOD: リソース制約下での軽量物体検出（Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages）</news:title>
   <news:publication_date>2026-05-31T08:33:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696267</loc>
  <lastmod>2026-05-31T08:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習に基づくIoTセキュリティ技術（IoT Security Techniques Based on Machine Learning）</news:title>
   <news:publication_date>2026-05-31T08:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696265</loc>
  <lastmod>2026-05-31T08:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドソース部分ランキングのマージンベースMLE（A Margin-based MLE for Crowdsourced Partial Ranking）</news:title>
   <news:publication_date>2026-05-31T08:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696263</loc>
  <lastmod>2026-05-31T08:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>負荷変動下における配電系統の最適タップ設定（Optimal Tap Setting of Voltage Regulation Transformers Using Batch Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-31T08:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696261</loc>
  <lastmod>2026-05-31T08:31:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全方位（360°）映像の品質評価と人の視線行動を結びつける研究（Bridge the Gap Between VQA and Human Behavior on Omnidirectional Video）</news:title>
   <news:publication_date>2026-05-31T08:31:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696259</loc>
  <lastmod>2026-05-31T08:31:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイドキック方策学習による能動視覚探索（Sidekick Policy Learning for Active Visual Exploration）</news:title>
   <news:publication_date>2026-05-31T08:31:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696257</loc>
  <lastmod>2026-05-31T08:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移における極端なクエーサー（Extreme quasars at high redshift）</news:title>
   <news:publication_date>2026-05-31T08:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696255</loc>
  <lastmod>2026-05-31T07:40:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>酸素空孔（F-center）が語るα-アルミナの光学と電子（Charge transition levels and optical properties of oxygen vacancies in α-alumina）</news:title>
   <news:publication_date>2026-05-31T07:40:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696253</loc>
  <lastmod>2026-05-31T07:40:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テラヘルツ帯ナノ通信における変調モード検出と変調分類（Modulation Mode Detection &amp;amp; Classification for in-Vivo Nano-Scale Communication Systems Operating in Terahertz Band）</news:title>
   <news:publication_date>2026-05-31T07:40:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696251</loc>
  <lastmod>2026-05-31T07:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクター中心関係ネットワークによる行動検出の革新（Actor-Centric Relation Network）</news:title>
   <news:publication_date>2026-05-31T07:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696249</loc>
  <lastmod>2026-05-31T07:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PROPEL: CNNの確率的パラメトリック回帰損失（PROPEL: Probabilistic Parametric Regression Loss for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-31T07:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696247</loc>
  <lastmod>2026-05-31T07:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空ネットワークの回復力（Resilience of Airborne Networks）</news:title>
   <news:publication_date>2026-05-31T07:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696245</loc>
  <lastmod>2026-05-31T07:39:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改善された逐次決定論的点過程による教師付き動画要約（Improved Sequential Determinantal Point Processes for Supervised Video Summarization）</news:title>
   <news:publication_date>2026-05-31T07:39:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696243</loc>
  <lastmod>2026-05-31T07:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群スパースSVDモデルとその生物学データへの応用 (Group-sparse SVD Models and Their Applications in Biological Data)</news:title>
   <news:publication_date>2026-05-31T07:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696241</loc>
  <lastmod>2026-05-31T06:48:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的スパイキングニューラルネットワークによるイベントカメラの光学フロー学習（Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception）</news:title>
   <news:publication_date>2026-05-31T06:48:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696239</loc>
  <lastmod>2026-05-31T06:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>駅単位自転車利用予測を変える多重グラフ畳み込みネットワーク（Bike Flow Prediction with Multi-Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-05-31T06:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696237</loc>
  <lastmod>2026-05-31T06:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データで葉を1枚ずつ切り分ける技術（Deep Leaf Segmentation Using Synthetic Data）</news:title>
   <news:publication_date>2026-05-31T06:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696235</loc>
  <lastmod>2026-05-31T06:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙画像から小惑星を自動検出するCNNの実装と成果（Detecting solar system objects with convolutional neural networks）</news:title>
   <news:publication_date>2026-05-31T06:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696233</loc>
  <lastmod>2026-05-31T06:47:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度視覚分類におけるメタ学習と補助データ選択（Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data）</news:title>
   <news:publication_date>2026-05-31T06:47:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696231</loc>
  <lastmod>2026-05-31T06:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>循環生成ネットワークを用いる教師なし敵対的深度推定（Unsupervised Adversarial Depth Estimation using Cycled Generative Networks）</news:title>
   <news:publication_date>2026-05-31T06:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696229</loc>
  <lastmod>2026-05-31T06:46:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース性学習に基づくグラントフリー大規模デバイス多元接続の多元検出（Sparsity Learning Based Multiuser Detection in Grant-Free Massive-Device Multiple Access）</news:title>
   <news:publication_date>2026-05-31T06:46:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696227</loc>
  <lastmod>2026-05-31T05:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的零空間における最大マージン尺度学習（Nullspace Kernel Maximum Margin Metric Learning）</news:title>
   <news:publication_date>2026-05-31T05:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696225</loc>
  <lastmod>2026-05-31T05:54:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SEAモデルによる熱需要予測の統合手法（SEA: A Combined Model for Heat Demand Prediction）</news:title>
   <news:publication_date>2026-05-31T05:54:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696223</loc>
  <lastmod>2026-05-31T05:54:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識における未対応テキスト活用──バックトランスレーション型データ増強（BACK-TRANSLATION-STYLE DATA AUGMENTATION FOR END-TO-END ASR）</news:title>
   <news:publication_date>2026-05-31T05:54:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696221</loc>
  <lastmod>2026-05-31T05:53:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのデバッグにおけるカバレッジ指向ファジング（TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing）</news:title>
   <news:publication_date>2026-05-31T05:53:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696219</loc>
  <lastmod>2026-05-31T05:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部位間の注意機構で人と物の関係を見抜く（Pairwise Body-Part Attention for Recognizing Human-Object Interactions）</news:title>
   <news:publication_date>2026-05-31T05:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696217</loc>
  <lastmod>2026-05-31T05:52:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アフィン部分空間のグラスマン多様体が変える幾何と計算基盤（The Grassmannian of Affine Subspaces）</news:title>
   <news:publication_date>2026-05-31T05:52:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696215</loc>
  <lastmod>2026-05-31T05:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>輸送手段分類における特徴量エンジニアリングの応用（TRANSPORTATION MODES CLASSIFICATION USING FEATURE ENGINEERING）</news:title>
   <news:publication_date>2026-05-31T05:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696213</loc>
  <lastmod>2026-05-31T05:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接続学習によるネットワーク設計最適化（MaskConnect: Connectivity Learning by Gradient Descent）</news:title>
   <news:publication_date>2026-05-31T05:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696211</loc>
  <lastmod>2026-05-31T05:01:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理における深層学習の利用調査（A Survey of the Usages of Deep Learning for Natural Language Processing）</news:title>
   <news:publication_date>2026-05-31T05:01:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696209</loc>
  <lastmod>2026-05-31T05:01:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ化点過程による人間行動パターンの学習（Learning Human Activity Patterns using Clustered Point Processes with Active and Inactive States）</news:title>
   <news:publication_date>2026-05-31T05:01:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696207</loc>
  <lastmod>2026-05-31T05:00:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超短エコー時間MRからのCT合成をCNNで実現する方法（Synthesizing CT from Ultrashort Echo-Time MR Images via Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-31T05:00:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696205</loc>
  <lastmod>2026-05-31T05:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成長温度が決める酸化物界面の伝導特性（Growth-Temperature Dependence of Conductivity at the LaCrO3/SrTiO3 (001) Interface）</news:title>
   <news:publication_date>2026-05-31T05:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696203</loc>
  <lastmod>2026-05-31T05:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep nested level setsによる心臓MR自動セグメンテーション（Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension）</news:title>
   <news:publication_date>2026-05-31T05:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696201</loc>
  <lastmod>2026-05-31T04:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D遊走するがん細胞の形態動態（The morphodynamics of 3D migrating cancer cells）</news:title>
   <news:publication_date>2026-05-31T04:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696199</loc>
  <lastmod>2026-05-31T04:08:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GFNによる画像の同時復元（Gated Fusion Network for Joint Image Deblurring and Super-Resolution）</news:title>
   <news:publication_date>2026-05-31T04:08:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696197</loc>
  <lastmod>2026-05-31T04:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CASED：極端なクラス不均衡に対するカリキュラム適応サンプリング（CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance）</news:title>
   <news:publication_date>2026-05-31T04:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696195</loc>
  <lastmod>2026-05-31T04:08:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造LSTMと構造化アテンションによるタンパク質相互作用抽出（Identifying Protein-Protein Interaction using Tree LSTM and Structured Attention）</news:title>
   <news:publication_date>2026-05-31T04:08:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696193</loc>
  <lastmod>2026-05-31T04:07:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>追加の言語情報を用いたニューラルシーケンスラベリングの改善 (Improving Neural Sequence Labelling using Additional Linguistic Information)</news:title>
   <news:publication_date>2026-05-31T04:07:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696191</loc>
  <lastmod>2026-05-31T04:07:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光量子コンピュータにおける状態準備とゲート合成のための機械学習手法（Machine learning method for state preparation and gate synthesis on photonic quantum computers）</news:title>
   <news:publication_date>2026-05-31T04:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696189</loc>
  <lastmod>2026-05-31T04:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>理論駆動型機械学習によるワンショット近最適トポロジ生成（One-Shot Generation of Near-Optimal Topology through Theory-Driven Machine Learning）</news:title>
   <news:publication_date>2026-05-31T04:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696187</loc>
  <lastmod>2026-05-31T04:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブーストしたH→b b̄を機械学習で強化する（Boosting H →b¯b with Machine Learning）</news:title>
   <news:publication_date>2026-05-31T04:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696185</loc>
  <lastmod>2026-05-31T03:15:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で曲率を求めるVOF法の革新（Computing Curvature for Volume of Fluid Methods using Machine Learning）</news:title>
   <news:publication_date>2026-05-31T03:15:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696183</loc>
  <lastmod>2026-05-31T03:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注釈なしで形状と外観モデルを学習するアルゴリズム（An Algorithm for Learning Shape and Appearance Models without Annotations）</news:title>
   <news:publication_date>2026-05-31T03:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696181</loc>
  <lastmod>2026-05-31T03:15:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>恒星磁場測定における機械学習アルゴリズムの利用法（On the use of machine learning algorithms in the measurement of stellar magnetic fields）</news:title>
   <news:publication_date>2026-05-31T03:15:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696179</loc>
  <lastmod>2026-05-31T03:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生データからのエンドツーエンド深層学習による着用型デバイスでの心房細動検出（End-to-end Deep Learning from Raw Sensor Data: Atrial Fibrillation Detection using Wearables）</news:title>
   <news:publication_date>2026-05-31T03:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696177</loc>
  <lastmod>2026-05-31T03:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的表面最適化を用いた密度推定（Deep PDF: Probabilistic Surface Optimization and Density Estimation）</news:title>
   <news:publication_date>2026-05-31T03:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696175</loc>
  <lastmod>2026-05-31T03:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化された単一イオンチャネル・ホジキン・ハクスリー・モデル（Quantized Single-Ion-Channel Hodgkin-Huxley Model for Quantum Neurons）</news:title>
   <news:publication_date>2026-05-31T03:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696173</loc>
  <lastmod>2026-05-31T03:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚用ダーモスコピー画像における病変領域検出の深層学習（Deep Learning Methods and Applications for Region of Interest Detection in Dermoscopic Images）</news:title>
   <news:publication_date>2026-05-31T03:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696171</loc>
  <lastmod>2026-05-31T02:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGAで実行するマルチスレッドCから合成したCNN推論アクセラレータ（FPGA-Based CNN Inference Accelerator Synthesized from Multi-Threaded C Software）</news:title>
   <news:publication_date>2026-05-31T02:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696169</loc>
  <lastmod>2026-05-31T02:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無限混合型逆ディリクレ分布モデル（Infinite Mixture of Inverted Dirichlet Distributions）</news:title>
   <news:publication_date>2026-05-31T02:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696167</loc>
  <lastmod>2026-05-31T02:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話システムにおけるドメイン外文検出をドメイン内文のみで学ぶ手法（Neural sentence embedding using only in-domain sentences for out-of-domain sentence detection in dialog systems）</news:title>
   <news:publication_date>2026-05-31T02:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696165</loc>
  <lastmod>2026-05-31T02:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きボルツマンマシンとニューラルネットワークによる潜在真実発見（Combining Restricted Boltzmann Machines with Neural Networks for Latent Truth Discovery）</news:title>
   <news:publication_date>2026-05-31T02:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696163</loc>
  <lastmod>2026-05-31T02:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オーバーフライ法によるニューラルネットワーク学習の力学系的視点（On the Overfly Algorithm in Deep Learning of Neural Networks）</news:title>
   <news:publication_date>2026-05-31T02:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696161</loc>
  <lastmod>2026-05-31T02:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波面制御によるラマン散乱光の深部検出強化（Enhanced deep detection of Raman scattered light by wavefront shaping）</news:title>
   <news:publication_date>2026-05-31T02:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696159</loc>
  <lastmod>2026-05-31T02:21:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務者のための学習可能性論争の整理（Learnable: Theory vs Applications）</news:title>
   <news:publication_date>2026-05-31T02:21:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696157</loc>
  <lastmod>2026-05-31T01:29:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念タグ付けとNLUの二十五年（Concept Tagging for Natural Language Understanding: Two Decadelong Algorithm Development）</news:title>
   <news:publication_date>2026-05-31T01:29:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696155</loc>
  <lastmod>2026-05-31T01:29:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超金属欠乏矮小銀河ドレコIIの詳細光学・分光解析（Pristine Dwarf-Galaxy Survey I: A detailed photometric and spectroscopic study of the very metal-poor Draco II satellite）</news:title>
   <news:publication_date>2026-05-31T01:29:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696153</loc>
  <lastmod>2026-05-31T01:28:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模MR由来心臓運動アトラスを用いた臨床情報と運動記述子の関連学習（Learning associations between clinical information and motion-based descriptors using a large scale MR-derived cardiac motion atlas）</news:title>
   <news:publication_date>2026-05-31T01:28:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696151</loc>
  <lastmod>2026-05-31T01:28:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子オートエンコーダの実験実装（Experimental Implementation of a Quantum Autoencoder via Quantum Adders）</news:title>
   <news:publication_date>2026-05-31T01:28:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696149</loc>
  <lastmod>2026-05-31T01:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測されない意図を暴く：協調行動とサイド情報を結びつける手法（Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge）</news:title>
   <news:publication_date>2026-05-31T01:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696147</loc>
  <lastmod>2026-05-31T01:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wandzura–Wilczek型近似による半包絡的深非弾性散乱の包括的記述（Semi-inclusive deep-inelastic scattering in Wandzura–Wilczek-type approximation）</news:title>
   <news:publication_date>2026-05-31T01:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696145</loc>
  <lastmod>2026-05-31T01:27:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期層における不変性を可視化する手法（Diverse feature visualizations reveal invariances in early layers of deep neural networks）</news:title>
   <news:publication_date>2026-05-31T01:27:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696143</loc>
  <lastmod>2026-05-31T00:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度組織画像分類を改善する深層空間融合ネットワーク（Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network）</news:title>
   <news:publication_date>2026-05-31T00:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696141</loc>
  <lastmod>2026-05-31T00:36:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原始的な超低質量星と褐色矮星の人口解析（Primeval very low-mass stars and brown dwarfs – IV. New L subdwarfs, Gaia astrometry, population properties, and a blue brown dwarf binary）</news:title>
   <news:publication_date>2026-05-31T00:36:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696139</loc>
  <lastmod>2026-05-31T00:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己符号化変分ニューラル機械翻訳（Auto-Encoding Variational Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-31T00:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696137</loc>
  <lastmod>2026-05-31T00:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電気機械工学におけるモデリング能力の構造と形成（COMPETENCE OF BACHELOR IN ELECTROMECHANICS IN SIMULATION）</news:title>
   <news:publication_date>2026-05-31T00:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696135</loc>
  <lastmod>2026-05-31T00:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的文脈認識ニューラルモデルのアプローチ（A Hierarchical Approach to Neural Context-Aware Modeling）</news:title>
   <news:publication_date>2026-05-31T00:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696133</loc>
  <lastmod>2026-05-31T00:35:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CMS実験における検出器監視の自動化と異常検出（Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron Collider）</news:title>
   <news:publication_date>2026-05-31T00:35:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696131</loc>
  <lastmod>2026-05-31T00:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CrossNetによる参照画像ベース超解像（CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping）</news:title>
   <news:publication_date>2026-05-31T00:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696129</loc>
  <lastmod>2026-05-30T23:44:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンド制限ベクトル場で効率化したPDE拘束LDDMM（Efficient Gauss-Newton-Krylov momentum conservation constrained PDE-LDDMM using the band-limited vector field parameterization）</news:title>
   <news:publication_date>2026-05-30T23:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696127</loc>
  <lastmod>2026-05-30T23:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次規則性グラフの系（ON A FAMILY OF HIGHLY REGULAR GRAPHS BY BROUWER, IVANOV, AND KLIN）</news:title>
   <news:publication_date>2026-05-30T23:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696125</loc>
  <lastmod>2026-05-30T23:43:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフにおけるリンク予測の全体評価と局所評価—ニューラル埋め込みのグローバル訓練の有用性（Global and local evaluation of link prediction tasks with neural embeddings）</news:title>
   <news:publication_date>2026-05-30T23:43:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696123</loc>
  <lastmod>2026-05-30T23:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>5Gにおける早期HARQフィードバック予測のための機械学習（Machine Learning for Early HARQ Feedback Prediction in 5G）</news:title>
   <news:publication_date>2026-05-30T23:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696121</loc>
  <lastmod>2026-05-30T23:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木星の中規模波動の5µm観測が示すもの（Jupiter’s mesoscale waves at 5 µm）</news:title>
   <news:publication_date>2026-05-30T23:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696119</loc>
  <lastmod>2026-05-30T23:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepLinkによるリンク予測の新枠組み（DeepLink: A Novel Link Prediction Framework based on Deep Learning）</news:title>
   <news:publication_date>2026-05-30T23:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696117</loc>
  <lastmod>2026-05-30T23:40:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プル型メッセージ伝搬による非パラメトリック信念伝播の効率化（Pull Message Passing for Nonparametric Belief Propagation）</news:title>
   <news:publication_date>2026-05-30T23:40:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696115</loc>
  <lastmod>2026-05-30T22:47:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNの振る舞いを解きほぐす：Excitable Network Attractorsによる機構的解釈（Interpreting recurrent neural networks behaviour via excitable network attractors）</news:title>
   <news:publication_date>2026-05-30T22:47:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696113</loc>
  <lastmod>2026-05-30T22:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンワールドにおける敵対的な人物再識別の枠組み（Adversarial Open-World Person Re-Identification）</news:title>
   <news:publication_date>2026-05-30T22:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696111</loc>
  <lastmod>2026-05-30T22:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測者を用いる機械学習が複雑な時空間挙動を予測する（Machine learning with observers predicts complex spatiotemporal behavior）</news:title>
   <news:publication_date>2026-05-30T22:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696109</loc>
  <lastmod>2026-05-30T22:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽観的No-Regretによる最適化加速（Acceleration through Optimistic No-Regret Dynamics）</news:title>
   <news:publication_date>2026-05-30T22:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696107</loc>
  <lastmod>2026-05-30T22:44:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損を許容するマルチモダリティ感情データの半教師あり生成モデル（Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data）</news:title>
   <news:publication_date>2026-05-30T22:44:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696105</loc>
  <lastmod>2026-05-30T22:44:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺癌組織の自動診断を支える深層学習フレームワーク（A Deep Learning Framework for Automatic Diagnosis in Lung Cancer）</news:title>
   <news:publication_date>2026-05-30T22:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696103</loc>
  <lastmod>2026-05-30T22:44:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AXNet：エンドツーエンドで学習可能な近似計算用ニューラルネットワーク（AXNet: ApproXimate computing using an end-to-end trainable neural network）</news:title>
   <news:publication_date>2026-05-30T22:44:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696101</loc>
  <lastmod>2026-05-30T21:50:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rob-GANによる生成器・識別器・敵対的攻撃の統合（Rob-GAN: Generator, Discriminator, and Adversarial Attacker）</news:title>
   <news:publication_date>2026-05-30T21:50:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696099</loc>
  <lastmod>2026-05-30T21:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>METTLEによる教師なし学習システムの評価法（METTLE: a METamorphic Testing approach to assessing and validating unsupervised machine LEarning systems）</news:title>
   <news:publication_date>2026-05-30T21:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696097</loc>
  <lastmod>2026-05-30T21:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なMRIコントラストを用いた視床の自動分割（A multi-contrast MRI approach to thalamus segmentation）</news:title>
   <news:publication_date>2026-05-30T21:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696095</loc>
  <lastmod>2026-05-30T21:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Opcode密度とSVMを用いたCrypto-Ransomware検出（Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware）</news:title>
   <news:publication_date>2026-05-30T21:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696093</loc>
  <lastmod>2026-05-30T21:47:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドでのDDoS検出のためのアンサンブル型マルチフィルタ特徴選択手法 (Ensemble-based Multi-Filter Feature Selection Method for DDoS Detection in Cloud Computing)</news:title>
   <news:publication_date>2026-05-30T21:47:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696091</loc>
  <lastmod>2026-05-30T21:47:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Windowsランサムウェアのネットワークトラフィック検出における機械学習の活用（Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection）</news:title>
   <news:publication_date>2026-05-30T21:47:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696089</loc>
  <lastmod>2026-05-30T21:46:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドソーシングにおける作業推薦—学習型の嗜好と信頼性の推定（Task Recommendation in Crowdsourcing Based on Learning Preferences and Reliabilities）</news:title>
   <news:publication_date>2026-05-30T21:46:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696087</loc>
  <lastmod>2026-05-30T20:54:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車車間（V2V）遭遇シナリオを交通プリミティブで理解する（Understanding V2V Driving Scenarios through Traffic Primitives）</news:title>
   <news:publication_date>2026-05-30T20:54:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696085</loc>
  <lastmod>2026-05-30T20:54:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークのためのシンボリック実行（Symbolic Execution for Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-30T20:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696083</loc>
  <lastmod>2026-05-30T20:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視線・シーン・注目のつながり：視線とシーンのサリエンシーを共同モデル化した一般化注目推定（Connecting Gaze, Scene, and Attention: Generalized Attention Estimation via Joint Modeling of Gaze and Scene Saliency）</news:title>
   <news:publication_date>2026-05-30T20:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696081</loc>
  <lastmod>2026-05-30T20:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トポロジカル・パーシステンス図の摂動頑健表現（Perturbation Robust Representations of Topological Persistence Diagrams）</news:title>
   <news:publication_date>2026-05-30T20:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696079</loc>
  <lastmod>2026-05-30T20:51:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>W-TALC: 弱教師付きによる時系列活動の局所化と分類（W-TALC: Weakly-supervised Temporal Activity Localization and Classification）</news:title>
   <news:publication_date>2026-05-30T20:51:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696077</loc>
  <lastmod>2026-05-30T20:51:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから現実への制御ポリシー適応（Adapting control policies from simulation to reality using a pairwise loss）</news:title>
   <news:publication_date>2026-05-30T20:51:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696075</loc>
  <lastmod>2026-05-30T20:51:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による銀河形態分類の自動化（Deep Learning for Galaxy Morphology Classification）</news:title>
   <news:publication_date>2026-05-30T20:51:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696073</loc>
  <lastmod>2026-05-30T19:57:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共通エントロピーを用いた因果推論の応用（Applications of Common Entropy for Causal Inference）</news:title>
   <news:publication_date>2026-05-30T19:57:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696071</loc>
  <lastmod>2026-05-30T19:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>筆跡認証の“全員対応”モデルが示す効率化の可能性（A writer-independent approach for offline signature verification using deep convolutional neural networks features）</news:title>
   <news:publication_date>2026-05-30T19:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696069</loc>
  <lastmod>2026-05-30T19:57:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線における肺結節検出で偽陽性を減らすための負例能動採掘（False Positive Reduction by Actively Mining Negative Samples for Pulmonary Nodule Detection in Chest Radiographs）</news:title>
   <news:publication_date>2026-05-30T19:57:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696067</loc>
  <lastmod>2026-05-30T19:56:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統合型マルチビュー低ランク回帰（Integrative Multi-View Reduced-Rank Regression）</news:title>
   <news:publication_date>2026-05-30T19:56:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696065</loc>
  <lastmod>2026-05-30T19:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラジオ銀河の自動形態分類を実現したFIRST Classifier（The FIRST Classifier: Compact and Extended Radio Galaxy Classification using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-30T19:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696063</loc>
  <lastmod>2026-05-30T19:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D ToFセンサ誤差を学習で補正する手法とFLATデータセット（Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset）</news:title>
   <news:publication_date>2026-05-30T19:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696061</loc>
  <lastmod>2026-05-30T19:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光流のための条件付き事前分布ネットワーク（Conditional Prior Networks for Optical Flow）</news:title>
   <news:publication_date>2026-05-30T19:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696059</loc>
  <lastmod>2026-05-30T19:02:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習潜在空間におけるロボット軌道計画（Robot Motion Planning in Learned Latent Spaces）</news:title>
   <news:publication_date>2026-05-30T19:02:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696057</loc>
  <lastmod>2026-05-30T19:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スループットポリマー探索のためのメッセージパッシングニューラルネットワーク（Message-passing neural networks for high-throughput polymer screening）</news:title>
   <news:publication_date>2026-05-30T19:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696055</loc>
  <lastmod>2026-05-30T19:01:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEデュアルフェーズ遠地検出器の設計（The DUNE Far Detector Interim Design Report Volume 3: Dual-Phase Module）</news:title>
   <news:publication_date>2026-05-30T19:01:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696053</loc>
  <lastmod>2026-05-30T19:00:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEファー検出器 中間設計報告（The DUNE Far Detector Interim Design Report, Volume 2: Single-Phase Module）</news:title>
   <news:publication_date>2026-05-30T19:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696051</loc>
  <lastmod>2026-05-30T18:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>投影モードを用いた選択的クラスタリング注釈（Selective Clustering Annotated using Modes of Projections）</news:title>
   <news:publication_date>2026-05-30T18:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696049</loc>
  <lastmod>2026-05-30T18:59:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的画像の普遍的検出指標（A General Metric for Identifying Adversarial Images）</news:title>
   <news:publication_date>2026-05-30T18:59:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696047</loc>
  <lastmod>2026-05-30T18:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNE遠隔検出器暫定設計報告の要点（The DUNE Far Detector Interim Design Report）</news:title>
   <news:publication_date>2026-05-30T18:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696045</loc>
  <lastmod>2026-05-30T18:05:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Privileged Informationを用いた識別的マルチビュー画像再ランキング（Discriminative multi-view Privileged Information learning for image re-ranking）</news:title>
   <news:publication_date>2026-05-30T18:05:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696043</loc>
  <lastmod>2026-05-30T18:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核子海におけるクォーク・反クォークのヘリシティ分布の非対称性（Quark-antiquark asymmetry of helicity distributions in the nucleon sea）</news:title>
   <news:publication_date>2026-05-30T18:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696041</loc>
  <lastmod>2026-05-30T18:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元モデル表現（HDMR）をガラスボックスとして使う意義（High Dimensional Model Representation as a Glass Box in Supervised Machine Learning）</news:title>
   <news:publication_date>2026-05-30T18:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696039</loc>
  <lastmod>2026-05-30T18:02:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合種別制限付き放射分布関数による高精度な原子化エネルギー予測（Bond type restricted radial distribution functions for accurate machine learning prediction of atomization energies）</news:title>
   <news:publication_date>2026-05-30T18:02:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696037</loc>
  <lastmod>2026-05-30T18:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分的オプション発見（Variational Option Discovery Algorithms）</news:title>
   <news:publication_date>2026-05-30T18:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/696035</loc>
  <lastmod>2026-05-30T18:01:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味論的に有意義な視点選択（Semantically Meaningful View Selection）</news:title>
   <news:publication_date>2026-05-30T18:01:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696033</loc>
  <lastmod>2026-05-30T18:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる物理概念の発見（Discovering physical concepts with neural networks）</news:title>
   <news:publication_date>2026-05-30T18:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696031</loc>
  <lastmod>2026-05-30T17:08:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団における衝突性質と非衝突性質の質量分解（DISSECTION OF THE COLLISIONAL AND COLLISIONLESS MASS COMPONENTS）</news:title>
   <news:publication_date>2026-05-30T17:08:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696029</loc>
  <lastmod>2026-05-30T17:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左側側頭新皮質のリップル振動と言語的エピソード記憶の障害（Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding）</news:title>
   <news:publication_date>2026-05-30T17:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696027</loc>
  <lastmod>2026-05-30T17:06:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的ロジットペアリングの堅牢性評価と理解（Evaluating and Understanding the Robustness of Adversarial Logit Pairing）</news:title>
   <news:publication_date>2026-05-30T17:06:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696025</loc>
  <lastmod>2026-05-30T17:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低次元単語ベース線形分類器の学習とAdaBag Lasso（LEARNING LOW DIMENSIONAL WORD BASED LINEAR CLASSIFIERS USING DATA SHARED ADAPTIVE BOOTSTRAP AGGREGATED LASSO）</news:title>
   <news:publication_date>2026-05-30T17:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696023</loc>
  <lastmod>2026-05-30T17:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像から層構造のある3D表現を推定する手法（Layer-structured 3D Scene Inference via View Synthesis）</news:title>
   <news:publication_date>2026-05-30T17:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696021</loc>
  <lastmod>2026-05-30T17:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前提選択と分散表現を用いたニューラルネットワーク（Premise selection with neural networks and distributed representation of features）</news:title>
   <news:publication_date>2026-05-30T17:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696019</loc>
  <lastmod>2026-05-30T17:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D顔生成のための畳み込みメッシュオートエンコーダ（Generating 3D faces using Convolutional Mesh Autoencoders）</news:title>
   <news:publication_date>2026-05-30T17:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696017</loc>
  <lastmod>2026-05-30T16:10:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Aggregated Learning（Aggregated Learning: A Deep Learning Framework Based on Information-Bottleneck Vector Quantization）</news:title>
   <news:publication_date>2026-05-30T16:10:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696015</loc>
  <lastmod>2026-05-30T16:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資源（データ）最適化が切り拓くニューラル固有表現抽出の実利（Resource-Size matters: Improving Neural Named Entity Recognition with Optimized Large Corpora）</news:title>
   <news:publication_date>2026-05-30T16:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696013</loc>
  <lastmod>2026-05-30T16:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模近傍統計に基づくシード付きグラフマッチング（Seeded Graph Matching via Large Neighborhood Statistics）</news:title>
   <news:publication_date>2026-05-30T16:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696011</loc>
  <lastmod>2026-05-30T16:02:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新奇検出が衝突型物理に切り開く可能性（Novelty Detection Meets Collider Physics）</news:title>
   <news:publication_date>2026-05-30T16:02:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696009</loc>
  <lastmod>2026-05-30T16:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作り特徴量から深層ローカル特徴へ（From handcrafted to deep local features）</news:title>
   <news:publication_date>2026-05-30T16:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696007</loc>
  <lastmod>2026-05-30T15:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像の合成によるデータ拡張と匿名化（Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-30T15:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696005</loc>
  <lastmod>2026-05-30T15:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動制約付きマルコフ決定過程とカルバック＝ライブラー情報量コスト（Action-Constrained Markov Decision Processes With Kullback–Leibler Cost）</news:title>
   <news:publication_date>2026-05-30T15:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696003</loc>
  <lastmod>2026-05-30T15:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的接続が文化を収縮させる（Social Connection Induces Cultural Contraction: Evidence from Hyperbolic Embeddings of Social and Semantic Networks）</news:title>
   <news:publication_date>2026-05-30T15:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/696001</loc>
  <lastmod>2026-05-30T15:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSPINEによる腰椎画像解析の自動化（DEEP SPINE: AUTOMATED LUMBAR VERTEBRAL SEGMENTATION, DISC-LEVEL DESIGNATION, AND SPINAL STENOSIS GRADING USING DEEP LEARNING）</news:title>
   <news:publication_date>2026-05-30T15:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695999</loc>
  <lastmod>2026-05-30T15:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統一的知覚パースィングによるシーン理解（Unified Perceptual Parsing for Scene Understanding）</news:title>
   <news:publication_date>2026-05-30T15:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695997</loc>
  <lastmod>2026-05-30T15:03:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2つのカウンタが語るパリティゲームのからくり（A Parity Game Tale of Two Counters）</news:title>
   <news:publication_date>2026-05-30T15:03:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695995</loc>
  <lastmod>2026-05-30T15:03:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像データから生物学的パラメータを推定するためのガウス過程を用いた全域最適化（Global optimization using Gaussian Processes to estimate biological parameters from image data）</news:title>
   <news:publication_date>2026-05-30T15:03:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695993</loc>
  <lastmod>2026-05-30T15:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイル認識を組み込んだコンテンツ損失によるリアルタイムHDスタイル転送（A Style-Aware Content Loss for Real-time HD Style Transfer）</news:title>
   <news:publication_date>2026-05-30T15:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/695991</loc>
  <lastmod>2026-05-30T15:02:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きオンライン極限学習機を用いた頑健な追跡（Robust Tracking via Weighted Online Extreme Learning Machine）</news:title>
   <news:publication_date>2026-05-30T15:02:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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