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   <news:title>DAWNBENCHのTTA評価が示す現場での示唆（Analysis of DAWNBench: Time-to-Accuracy）</news:title>
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   <news:title>累積報酬を超えるバンディット枠組みの一般化（A General Framework for Bandit Problems Beyond Cumulative Objectives）</news:title>
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   <news:title>大規模な人間の移動データを用いた長期犯罪予測（Mining large-scale human mobility data for long-term crime prediction）</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>因子分解型敵対的ネットワークによる教師なしドメイン適応（Factorized Adversarial Networks for Unsupervised Domain Adaptation）</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>6つのニューロンでアタリを攻略する方法（Playing Atari with Six Neurons）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:genres>Blog</news:genres>
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   <news:title>前処理の違いを超えて学ぶ―前立腺組織スライド分類のための敵対的ドメイン適応（Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images）</news:title>
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   <news:title>InでドープしたZnO表面におけるCOおよびOH吸着の第一原理研究（First-principles study of CO and OH adsorption on In-doped ZnO surfaces）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>バックドロップ：確率的逆伝播の直感と実務的意義（Backdrop: Stochastic Backpropagation）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:genres>Blog</news:genres>
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   <news:title>プラトー関数の精密ランタイム解析（Precise Runtime Analysis for Plateau Functions）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>単純で強力な単語埋め込みの整列手法（Closed Form Word Embedding Alignment）</news:title>
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   <news:title>Next-Door解析によるポストモデル検討（Post model-fitting exploration via a “Next-Door” analysis）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>データ駆動による電力系の撹乱位置推定と大きさの推定（Data-driven Localization and Estimation of Disturbance in the Interconnected Power System）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>深層ニューラルネットワークにおけるフィッシャー情報の普遍統計（Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach）</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>Y-Net: 乳房生検画像のための同時セグメンテーションと分類（Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:language>ja</news:language>
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   <news:title>M33銀河におけるGMCスケールの星形成則（The star-formation law at GMC scales in M33, the Triangulum Galaxy）</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>脳線維配向のエンドツーエンド推定（End to End Brain Fiber Orientation Estimation Using Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-12T21:39:18Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単眼自己教師あり深度推定の深掘り（Digging Into Self-Supervised Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-05-12T21:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-12T21:38:46Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>学習で設計する非線形向け符号化（Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation）</news:title>
   <news:publication_date>2026-05-12T21:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>合意ベース学習（Agreement-based Learning）</news:title>
   <news:publication_date>2026-05-12T21:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>モメンタムと非同期の加速トレードオフ（Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Distributed Nonconvex Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-12T21:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:title>物理法則は反事実的通信を禁止しない（The laws of physics do not prohibit counterfactual communication）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>モバイル向けRNN圧縮の動的階層革新：DirNet（Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices）</news:title>
   <news:publication_date>2026-05-12T21:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:title>ML-Leaksによる学習データ漏洩の実態（ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models）</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>Deep Graphsの提案と意義（Deep Graphs）</news:title>
   <news:publication_date>2026-05-12T20:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689482</loc>
  <lastmod>2026-05-12T20:45:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディフェオモルフィック学習の要点と経営への示唆（Diffeomorphic Learning）</news:title>
   <news:publication_date>2026-05-12T20:45:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689480</loc>
  <lastmod>2026-05-12T20:45:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークによる学習可能な物理エンジン（Graph Networks as Learnable Physics Engines for Inference and Control）</news:title>
   <news:publication_date>2026-05-12T20:45:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689478</loc>
  <lastmod>2026-05-12T20:44:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元強化学習における進化戦略の課題（Challenges in High-dimensional Reinforcement Learning with Evolution Strategies）</news:title>
   <news:publication_date>2026-05-12T20:44:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689476</loc>
  <lastmod>2026-05-12T20:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼鏡耐性を持つ顔認識のための顔合成（Face Synthesis for Eyeglass-Robust Face Recognition）</news:title>
   <news:publication_date>2026-05-12T20:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689474</loc>
  <lastmod>2026-05-12T20:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セキュアデザイン教育によるサイバーセキュリティ人材育成（Novel Approach for Cybersecurity Workforce Development: A Course in Secure Design）</news:title>
   <news:publication_date>2026-05-12T20:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689472</loc>
  <lastmod>2026-05-12T20:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と機械における物理的構築のための関係性誘導バイアス（Relational inductive bias for physical construction in humans and machines）</news:title>
   <news:publication_date>2026-05-12T20:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689470</loc>
  <lastmod>2026-05-12T19:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>副作用の罰則に関するステップワイズ相対到達可能性（Penalizing side effects using stepwise relative reachability）</news:title>
   <news:publication_date>2026-05-12T19:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689468</loc>
  <lastmod>2026-05-12T19:52:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称相互制約を持つ深層連続条件付き確率場によるオンライン多物体追跡（Deep Continuous Conditional Random Fields with Asymmetric Inter-object Constraints for Online Multi-object Tracking）</news:title>
   <news:publication_date>2026-05-12T19:52:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689466</loc>
  <lastmod>2026-05-12T19:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dual-tree複素ウェーブレット変換のための勾配ベースフィルタ設計（Gradient-based Filter Design for the Dual-tree Wavelet Transform）</news:title>
   <news:publication_date>2026-05-12T19:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689464</loc>
  <lastmod>2026-05-12T19:50:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏極された深部散乱における電弱パラメータの決定（Determination of electroweak parameters in polarised deep-inelastic scattering at HERA）</news:title>
   <news:publication_date>2026-05-12T19:50:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689462</loc>
  <lastmod>2026-05-12T19:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互推薦のオンライン学習と理論的保証（Online Reciprocal Recommendation with Theoretical Performance Guarantees）</news:title>
   <news:publication_date>2026-05-12T19:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689460</loc>
  <lastmod>2026-05-12T19:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TDか否か：深層強化学習における時間差分の役割（TD OR NOT TD: ANALYZING THE ROLE OF TEMPORAL DIFFERENCING IN DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-05-12T19:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689458</loc>
  <lastmod>2026-05-12T19:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K-meansによる効率的かつ拡張性の高いバッチベイズ最適化（Efficient and Scalable Batch Bayesian Optimization Using K-Means）</news:title>
   <news:publication_date>2026-05-12T19:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689456</loc>
  <lastmod>2026-05-12T18:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天王星におけるメタン分布と極域の明るさ変化（THE METHANE DISTRIBUTION AND POLAR BRIGHTENING ON URANUS）</news:title>
   <news:publication_date>2026-05-12T18:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689454</loc>
  <lastmod>2026-05-12T18:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事例とプロトタイプから学ぶ分類の考え方（Learning from Exemplars and Prototypes in Machine Learning and Psychology）</news:title>
   <news:publication_date>2026-05-12T18:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689452</loc>
  <lastmod>2026-05-12T18:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストを脳地図に翻訳する手法（Text to brain: predicting the spatial distribution of neuroimaging observations from text reports）</news:title>
   <news:publication_date>2026-05-12T18:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689450</loc>
  <lastmod>2026-05-12T18:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列とニューラルネットによるRed Hatのボラティリティ解析（Non-linear Time Series and Artificial Neural Network of Red Hat Volatility）</news:title>
   <news:publication_date>2026-05-12T18:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689448</loc>
  <lastmod>2026-05-12T18:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存交絡因子の最適バランシングによる周辺構造モデルの改善（Optimal balancing of time-dependent confounders for marginal structural models）</news:title>
   <news:publication_date>2026-05-12T18:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689446</loc>
  <lastmod>2026-05-12T18:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ごとの定常ノイズを調整してICAを堅牢化する（Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise）</news:title>
   <news:publication_date>2026-05-12T18:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689444</loc>
  <lastmod>2026-05-12T18:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層多構造形状解析：神経解剖学への応用（Deep Multi-Structural Shape Analysis: Application to Neuroanatomy）</news:title>
   <news:publication_date>2026-05-12T18:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689442</loc>
  <lastmod>2026-05-12T18:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個体間公平性に基づくデータ表現学習の意義（iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making）</news:title>
   <news:publication_date>2026-05-12T18:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689440</loc>
  <lastmod>2026-05-12T18:03:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキサス・オクラホマ・カンザス州におけるPGA・PGV予測のためのニューラルネットワーク方程式（Neural Network-Based Equations for Predicting PGA and PGV in Texas, Oklahoma, and Kansas）</news:title>
   <news:publication_date>2026-05-12T18:03:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689438</loc>
  <lastmod>2026-05-12T18:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RedNet：残差エンコーダ・デコーダによる屋内RGB-Dセマンティックセグメンテーション（RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-12T18:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689436</loc>
  <lastmod>2026-05-12T18:01:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペロブスカイト酸化物の熱力学的安定性予測（Predicting the thermodynamic stability of perovskite oxides using machine learning models）</news:title>
   <news:publication_date>2026-05-12T18:01:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689434</loc>
  <lastmod>2026-05-12T18:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症支援を目的としたモバイルアプリの実務的レビュー（Applications for mobile devices focused on support for autism spectrum disorder population and / or people in their immediate environment in their daily lives: a systematic and practical review from a Spanish-speaking perspective）</news:title>
   <news:publication_date>2026-05-12T18:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689432</loc>
  <lastmod>2026-05-12T18:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳画像データの規範的モデリングとスケーラブルなマルチタスクガウス過程（Normative Modeling of Neuroimaging Data using Scalable Multi-Task Gaussian Processes）</news:title>
   <news:publication_date>2026-05-12T18:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689430</loc>
  <lastmod>2026-05-12T18:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ユーザ向け多アンテナマルチキャストの遅延性能（Delay Performance of Multi-Antenna Multicasting in Wireless Networks）</news:title>
   <news:publication_date>2026-05-12T18:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689428</loc>
  <lastmod>2026-05-12T17:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵嚢胞の画像診断を変える一歩（Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks）</news:title>
   <news:publication_date>2026-05-12T17:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689426</loc>
  <lastmod>2026-05-12T17:08:23Z</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ポテンシャルと古典力場の適応結合（Adaptive coupling of a deep neural network potential to a classical force field）</news:title>
   <news:publication_date>2026-05-12T17:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689424</loc>
  <lastmod>2026-05-12T17:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形ヌーリングによるメタラーニングの考え方と実務的含意（Meta-Learner with Linear Nulling）</news:title>
   <news:publication_date>2026-05-12T17:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689422</loc>
  <lastmod>2026-05-12T17:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的二重レベル多目的進化による単層・多層エコーステートネットワーク自己符号化器の進化（Hierarchical Bi-level Multi-Objective Evolution of Single- and Multi-layer Echo State Network Autoencoders for Data Representations）</news:title>
   <news:publication_date>2026-05-12T17:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689420</loc>
  <lastmod>2026-05-12T17:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度マルチモードファイバー内視鏡による深部脳イメージングの進展（High-fidelity multimode fibre-based endoscopy for deep‑brain in vivo imaging）</news:title>
   <news:publication_date>2026-05-12T17:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689418</loc>
  <lastmod>2026-05-12T17:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造グラフ上の全変動正則化推定量の理論と実務的示唆（On the total variation regularized estimator over a class of tree graphs）</news:title>
   <news:publication_date>2026-05-12T17:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689416</loc>
  <lastmod>2026-05-12T17:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データで熱赤外（TIR）トラッキングを変える（Synthetic data generation for end-to-end thermal infrared tracking）</news:title>
   <news:publication_date>2026-05-12T17:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689414</loc>
  <lastmod>2026-05-12T16:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互評価から学ぶ分散学習（Distributed Learning from Interactions in Social Networks）</news:title>
   <news:publication_date>2026-05-12T16:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689412</loc>
  <lastmod>2026-05-12T16:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>提案したエポックとMFCC特徴を用いたDNN-HMMベースの話者適応感情認識（DNN-HMM based Speaker Adaptive Emotion Recognition using Proposed Epoch and MFCC Features）</news:title>
   <news:publication_date>2026-05-12T16:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689410</loc>
  <lastmod>2026-05-12T16:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所適応大マージンを導入する深層埋め込み学習（ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating）</news:title>
   <news:publication_date>2026-05-12T16:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689408</loc>
  <lastmod>2026-05-12T16:12:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れたカテゴリ変数の学習のための類似度エンコーディング (Similarity encoding for learning with dirty categorical variables)</news:title>
   <news:publication_date>2026-05-12T16:12:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689406</loc>
  <lastmod>2026-05-12T16:12:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークプロトコルの自動抽象化と弱教師ありクラスタリング（Automatic clustering of a network protocol with weakly-supervised clustering）</news:title>
   <news:publication_date>2026-05-12T16:12:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689404</loc>
  <lastmod>2026-05-12T16:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小平均の逐次検定：ThompsonからMurphyサンプリングへ（Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling）</news:title>
   <news:publication_date>2026-05-12T16:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689402</loc>
  <lastmod>2026-05-12T16:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師データなしで学習する画像デノイザ（Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior）</news:title>
   <news:publication_date>2026-05-12T16:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689400</loc>
  <lastmod>2026-05-12T15:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベートPAC学習は有限のLittlestone次元を示唆する（Private PAC learning implies finite Littlestone dimension）</news:title>
   <news:publication_date>2026-05-12T15:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689398</loc>
  <lastmod>2026-05-12T15:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配／ミラー降下法：ミニマックス最適性と暗黙の正則化（STOCHASTIC GRADIENT/MIRROR DESCENT: MINI-MAX OPTIMALITY AND IMPLICIT REGULARIZATION）</news:title>
   <news:publication_date>2026-05-12T15:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689396</loc>
  <lastmod>2026-05-12T15:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定化された自由空間光周波数伝送（Stabilized free-space optical frequency transfer）</news:title>
   <news:publication_date>2026-05-12T15:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689394</loc>
  <lastmod>2026-05-12T15:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小児X線画像におけるカテーテル自動検出（Automatic catheter detection in pediatric X-ray images using a scale-recurrent network and synthetic data）</news:title>
   <news:publication_date>2026-05-12T15:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689392</loc>
  <lastmod>2026-05-12T15:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィックニューラルアーキテクチャ（Holographic Neural Architectures）</news:title>
   <news:publication_date>2026-05-12T15:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689390</loc>
  <lastmod>2026-05-12T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚仕様からのプログラム合成（Program Synthesis from Visual Specification）</news:title>
   <news:publication_date>2026-05-12T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689388</loc>
  <lastmod>2026-05-12T15:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散計算の安全性と可用性を同時に高める設計 — Lagrange Coded Computing（Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy）</news:title>
   <news:publication_date>2026-05-12T15:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689386</loc>
  <lastmod>2026-05-12T14:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>伝統中国語向け読解データセットDRCDの構築と評価（DRCD: A Chinese Machine Reading Comprehension Dataset）</news:title>
   <news:publication_date>2026-05-12T14:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689384</loc>
  <lastmod>2026-05-12T14:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実に自信を持ち滑らかさを保つ学習（Adversarial confidence and smoothness regularizations for scalable unsupervised discriminative learning）</news:title>
   <news:publication_date>2026-05-12T14:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689382</loc>
  <lastmod>2026-05-12T14:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どれだけ共有するか？ポーカー風の選択的プライバシー保護フレームワーク（How Much Are You Willing to Share? A “Poker-Styled” Selective Privacy Preserving Framework for Recommender Systems）</news:title>
   <news:publication_date>2026-05-12T14:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689380</loc>
  <lastmod>2026-05-12T14:23:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ホモジニアスモデル学習におけるアルゴリズム的正則化（Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced）</news:title>
   <news:publication_date>2026-05-12T14:23:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689378</loc>
  <lastmod>2026-05-12T14:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価格が品質を示す場合の競争的価格形成（Competitive pricing despite search costs if lower price signals quality）</news:title>
   <news:publication_date>2026-05-12T14:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689376</loc>
  <lastmod>2026-05-12T14:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空画像のシーン分類における最近の進展と機会（RECENT ADVANCES AND OPPORTUNITIES IN SCENE CLASSIFICATION OF AERIAL IMAGES WITH DEEP MODELS）</news:title>
   <news:publication_date>2026-05-12T14:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689374</loc>
  <lastmod>2026-05-12T14:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ多発の医療テキストから誤綴りを掘る自動生成器（An unsupervised and customizable misspelling generator for mining noisy health-related text sources）</news:title>
   <news:publication_date>2026-05-12T14:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689372</loc>
  <lastmod>2026-05-12T13:31:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像と深層学習によるアフリカのインフラ品質評価（Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning）</news:title>
   <news:publication_date>2026-05-12T13:31:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689370</loc>
  <lastmod>2026-05-12T13:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SparkとMPIをつなぐ「Alchemist」の意義（Alchemist: An Apache Spark ⇔MPI Interface）</news:title>
   <news:publication_date>2026-05-12T13:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689368</loc>
  <lastmod>2026-05-12T13:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慎重な探索とインターリービングによる保守的探索（Conservative Exploration using Interleaving）</news:title>
   <news:publication_date>2026-05-12T13:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689366</loc>
  <lastmod>2026-05-12T13:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスタマイズされたデータ表現と近似計算の機械学習応用への展開 (Deploying Customized Data Representation and Approximate Computing in Machine Learning Applications)</news:title>
   <news:publication_date>2026-05-12T13:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689364</loc>
  <lastmod>2026-05-12T13:18:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成敵対ネットワークにおける分断された多様体学習（Disconnected Manifold Learning for Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-12T13:18:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689362</loc>
  <lastmod>2026-05-12T13:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント強化学習における二重平均化と双対最適化（Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization）</news:title>
   <news:publication_date>2026-05-12T13:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689360</loc>
  <lastmod>2026-05-12T13:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分解によるMVRチェーングラフの構造学習 (Structural Learning of MVR Chain Graphs via Decomposition)</news:title>
   <news:publication_date>2026-05-12T13:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689358</loc>
  <lastmod>2026-05-12T12:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構がメタラーニングにもたらす効果（On the Importance of Attention in Meta-Learning for Few-Shot Text Classification）</news:title>
   <news:publication_date>2026-05-12T12:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689356</loc>
  <lastmod>2026-05-12T12:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答における反例検出（On the Flip Side: Identifying Counterexamples in Visual Question Answering）</news:title>
   <news:publication_date>2026-05-12T12:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689354</loc>
  <lastmod>2026-05-12T12:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データからグラフを学習する：信号表現の視点（Learning graphs from data: A signal representation perspective）</news:title>
   <news:publication_date>2026-05-12T12:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689352</loc>
  <lastmod>2026-05-12T12:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TernausNetV2による衛星画像のインスタンス分割（TernausNetV2: Fully Convolutional Network for Instance Segmentation）</news:title>
   <news:publication_date>2026-05-12T12:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689350</loc>
  <lastmod>2026-05-12T12:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在木学習と微分可能パーサによる文表現（Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing）</news:title>
   <news:publication_date>2026-05-12T12:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689348</loc>
  <lastmod>2026-05-12T12:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像をConvNetで分類するCADシステムの研究（Study and development of a Computer-Aided Diagnosis system for classification of chest x-ray images using convolutional neural networks pre-trained for ImageNet and data augmentation）</news:title>
   <news:publication_date>2026-05-12T12:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689346</loc>
  <lastmod>2026-05-12T12:23:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BPjsによる反応型システムのモデリングフレームワーク（BPjs — a framework for modeling reactive systems using a scripting language and BP）</news:title>
   <news:publication_date>2026-05-12T12:23:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689344</loc>
  <lastmod>2026-05-12T11:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子位相転移の機械学習解析（Machine learning of quantum phase transitions）</news:title>
   <news:publication_date>2026-05-12T11:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689342</loc>
  <lastmod>2026-05-12T11:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低滑らかさ回帰関数に対する正則化Nyström部分サンプリングの解析（ANALYSIS OF REGULARIZED NYSTRÖM SUBSAMPLING FOR REGRESSION FUNCTIONS OF LOW SMOOTHNESS）</news:title>
   <news:publication_date>2026-05-12T11:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689340</loc>
  <lastmod>2026-05-12T11:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データの雑音と欠損を乗り越える行列因子分解による因果推論（Causal Inference with Noisy and Missing Covariates via Matrix Factorization）</news:title>
   <news:publication_date>2026-05-12T11:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689338</loc>
  <lastmod>2026-05-12T11:31:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AID++: 航空画像シーン分類のための大規模データセット更新（AID++: AN UPDATED VERSION OF AID ON SCENE CLASSIFICATION）</news:title>
   <news:publication_date>2026-05-12T11:31:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689336</loc>
  <lastmod>2026-05-12T11:31:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文の意味的埋め込みの学習（Learning Semantic Sentence Embeddings using Pair-wise Discriminator）</news:title>
   <news:publication_date>2026-05-12T11:31:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689334</loc>
  <lastmod>2026-05-12T11:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列MRIのk空間ディープラーニング（k-Space Deep Learning for Parallel MRI: Application to Time-Resolved MR Angiography）</news:title>
   <news:publication_date>2026-05-12T11:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689332</loc>
  <lastmod>2026-05-12T11:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非敵対的な教師なしドメイン写像（NAM: Non-Adversarial Unsupervised Domain Mapping）</news:title>
   <news:publication_date>2026-05-12T11:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689330</loc>
  <lastmod>2026-05-12T10:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロープレディクションによる光学フロー推定の進化（ProFlow: Learning to Predict Optical Flow）</news:title>
   <news:publication_date>2026-05-12T10:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689328</loc>
  <lastmod>2026-05-12T10:39:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャックナイフ経験的尤度によるギニ相関とその等価性検定（Jackknife Empirical Likelihood Methods for Gini Correlations and their Equality Testing）</news:title>
   <news:publication_date>2026-05-12T10:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689326</loc>
  <lastmod>2026-05-12T10:39:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標志向対話システムのための高度な対話マネージャ構築（Building Advanced Dialogue Managers for Goal-Oriented Dialogue Systems）</news:title>
   <news:publication_date>2026-05-12T10:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689324</loc>
  <lastmod>2026-05-12T10:38:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された強化学習における探索最小化（Exploration in Structured Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-12T10:38:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689322</loc>
  <lastmod>2026-05-12T10:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチキャスト注意機構による検索型質問応答と応答予測の革新（Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction）</news:title>
   <news:publication_date>2026-05-12T10:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689320</loc>
  <lastmod>2026-05-12T10:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローンによる実時間監視と暴力者検出（Eye in the Sky: Real-time Drone Surveillance System for Violent Individuals Identification）</news:title>
   <news:publication_date>2026-05-12T10:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689318</loc>
  <lastmod>2026-05-12T10:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双対‑原始グラフ畳み込みネットワーク（Dual-Primal Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-05-12T10:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689316</loc>
  <lastmod>2026-05-12T09:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像列から物語を紡ぐニューラル・ビジュアルストーリーテラー（Contextualize, Show and Tell: A Neural Visual Storyteller）</news:title>
   <news:publication_date>2026-05-12T09:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689314</loc>
  <lastmod>2026-05-12T09:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次近似で迫る統計的二値分類の限界（Second-Order Asymptotically Optimal Statistical Classification）</news:title>
   <news:publication_date>2026-05-12T09:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689312</loc>
  <lastmod>2026-05-12T09:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメトリック偏微分方程式のデータ駆動同定（Data-driven identification of parametric partial differential equations）</news:title>
   <news:publication_date>2026-05-12T09:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689310</loc>
  <lastmod>2026-05-12T09:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型アテンションによるソーシャル文脈画像推薦（A Hierarchical Attention Model for Social Contextual Image Recommendation）</news:title>
   <news:publication_date>2026-05-12T09:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689308</loc>
  <lastmod>2026-05-12T09:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ無しでソフトマックスを設計する発想（Data-Free/Data-Sparse Softmax Parameter Estimation with Structured Class Geometries）</news:title>
   <news:publication_date>2026-05-12T09:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689306</loc>
  <lastmod>2026-05-12T09:45:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小ノルム学習が示す過学習への解（Minnorm training: an algorithm for training over-parameterized deep neural networks）</news:title>
   <news:publication_date>2026-05-12T09:45:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689304</loc>
  <lastmod>2026-05-12T09:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳における密情報フロー（Dense Information Flow for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-12T09:45:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689302</loc>
  <lastmod>2026-05-12T08:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走行データから学習・一般化するモーションプリミティブ（Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applications）</news:title>
   <news:publication_date>2026-05-12T08:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689300</loc>
  <lastmod>2026-05-12T08:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データに効く分散型ガウス過程の整合化手法（Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression）</news:title>
   <news:publication_date>2026-05-12T08:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689298</loc>
  <lastmod>2026-05-12T08:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可解釈な階層的意味畳み込みニューラルネットワークによる肺結節悪性度分類（An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification）</news:title>
   <news:publication_date>2026-05-12T08:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689296</loc>
  <lastmod>2026-05-12T08:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライマル・デュアル Frank‑Wolfe による確率制約最適化の実務的示唆（Primal‑Dual Frank‑Wolfe for Constrained Stochastic Programs with Convex and Non‑convex Objectives）</news:title>
   <news:publication_date>2026-05-12T08:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689294</loc>
  <lastmod>2026-05-12T08:51:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレイヤー基底探索と効率的アルゴリズム（On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-12T08:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689292</loc>
  <lastmod>2026-05-12T08:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的注意機構を備えたリカレントハイウェイネットワークによる時系列予測（Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction）</news:title>
   <news:publication_date>2026-05-12T08:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689290</loc>
  <lastmod>2026-05-12T08:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティアフィールド銀河団 MACS J1149 の質量モデルの実務的示唆（MASS MODELING OF FRONTIER FIELDS CLUSTER MACS J1149.5+2223 USING STRONG AND WEAK LENSING）</news:title>
   <news:publication_date>2026-05-12T08:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689288</loc>
  <lastmod>2026-05-12T08:00:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Pepperに学ぶ棋譜と知識の融合――強化学習におけるExpert Iteration型チェスエージェントの要点（Deep Pepper: Expert Iteration based Chess agent in the Reinforcement Learning Setting）</news:title>
   <news:publication_date>2026-05-12T08:00:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689286</loc>
  <lastmod>2026-05-12T07:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所ニューラルネットワーク、非局所拡散と非局所モデリング (Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling)</news:title>
   <news:publication_date>2026-05-12T07:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689284</loc>
  <lastmod>2026-05-12T07:58:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的大規模グラフのリアルタイム監視の幾何学的手法（A Geometric Approach for Real-time Monitoring of Dynamic Large Scale Graphs）</news:title>
   <news:publication_date>2026-05-12T07:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689282</loc>
  <lastmod>2026-05-12T07:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>理想化モデルが敵対的事例を持たない十分条件（Sufficient Conditions for Idealised Models to Have No Adversarial Examples）</news:title>
   <news:publication_date>2026-05-12T07:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689280</loc>
  <lastmod>2026-05-12T07:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>厚さで制御されるスメクティック—ヘキサティック転移と三重点への近接（Evidence of a first-order smectic – hexatic transition and its proximity to tricritical point in smectic films）</news:title>
   <news:publication_date>2026-05-12T07:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689278</loc>
  <lastmod>2026-05-12T07:58:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯固定時間学習と最良一致検索の鍵（SPARSE DISTRIBUTED REPRESENTATION, HIERARCHY, CRITICAL PERIODS, METAPLASTICITY）</news:title>
   <news:publication_date>2026-05-12T07:58:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689276</loc>
  <lastmod>2026-05-12T07:57:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性下での最適クラスタリング（Optimal Clustering under Uncertainty）</news:title>
   <news:publication_date>2026-05-12T07:57:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689274</loc>
  <lastmod>2026-05-12T07:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所解釈可能モデルと監督付き分割による説明手法（Locally Interpretable Models and Effects based on Supervised Partitioning）</news:title>
   <news:publication_date>2026-05-12T07:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689272</loc>
  <lastmod>2026-05-12T07:05:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商用オークションデータのスクレイピングと前処理による詐欺検出基盤の作り方（Scraping and Preprocessing Commercial Auction Data for Fraud Classification）</news:title>
   <news:publication_date>2026-05-12T07:05:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689270</loc>
  <lastmod>2026-05-12T07:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計情報に依存しない直交マッチング追跡（Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit）</news:title>
   <news:publication_date>2026-05-12T07:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689268</loc>
  <lastmod>2026-05-12T07:04:15Z</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>2026-05-12T07:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689266</loc>
  <lastmod>2026-05-12T07:04:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶モデルに着想を得たRNNの新たな枠組み（A Novel Framework for Recurrent Neural Networks with Enhancing Information Processing and Transmission between Units）</news:title>
   <news:publication_date>2026-05-12T07:04:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689264</loc>
  <lastmod>2026-05-12T07:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間・時間の深層特徴空間におけるSqueeze-and-Excitationによる行動認識強化（Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition）</news:title>
   <news:publication_date>2026-05-12T07:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689262</loc>
  <lastmod>2026-05-12T07:03:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAQN: 深層オートエンコーダによる事前学習で強化学習の試行回数を削減する手法（DAQN: Deep Auto-encoder and Q-Network）</news:title>
   <news:publication_date>2026-05-12T07:03:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689260</loc>
  <lastmod>2026-05-12T06:12:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GamePad: 定理証明に機械学習を活かすための環境設計（GAMEPAD: A LEARNING ENVIRONMENT FOR THEOREM PROVING）</news:title>
   <news:publication_date>2026-05-12T06:12:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689258</loc>
  <lastmod>2026-05-12T06:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察から学ぶ内部モデルによる報酬設計（Internal Model from Observations for Reward Shaping）</news:title>
   <news:publication_date>2026-05-12T06:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689256</loc>
  <lastmod>2026-05-12T06:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック認識型生成対抗ネットワークによる胸部X線画像の教師なしドメイン適応（Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation）</news:title>
   <news:publication_date>2026-05-12T06:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689254</loc>
  <lastmod>2026-05-12T06:10:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>箱だけ注釈で医用画像を高精度に分割する方法（BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation）</news:title>
   <news:publication_date>2026-05-12T06:10:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689252</loc>
  <lastmod>2026-05-12T06:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多次元行動空間における政策勾配のための効率的エントロピー（Efficient Entropy for Policy Gradient with Multidimensional Action Space）</news:title>
   <news:publication_date>2026-05-12T06:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689250</loc>
  <lastmod>2026-05-12T06:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非IIDデータを扱う連合学習（Federated Learning with Non-IID Data）</news:title>
   <news:publication_date>2026-05-12T06:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689248</loc>
  <lastmod>2026-05-12T06:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T06:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689246</loc>
  <lastmod>2026-05-12T05:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダが生成線形モデルを学ぶ方法（Autoencoders Learn Generative Linear Models）</news:title>
   <news:publication_date>2026-05-12T05:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689244</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>敵対的例の検出を狙うKey-based Network（Detecting Adversarial Examples via Key-based Network）</news:title>
   <news:publication_date>2026-05-12T05:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689242</loc>
  <lastmod>2026-05-12T05:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブな位置情報付きマルチメディア検索の効率化（Efficient Interactive Search for Geo-tagged Multimedia Data）</news:title>
   <news:publication_date>2026-05-12T05:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689240</loc>
  <lastmod>2026-05-12T05:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内在等長多様体学習と屋内位置推定への応用（INTRINSIC ISOMETRIC MANIFOLD LEARNING WITH APPLICATION TO LOCALIZATION）</news:title>
   <news:publication_date>2026-05-12T05:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689238</loc>
  <lastmod>2026-05-12T05:16:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック学習における変数選択とパワーシリーズカーネル（Variable Selection for Nonparametric Learning with Power Series Kernels）</news:title>
   <news:publication_date>2026-05-12T05:16:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689236</loc>
  <lastmod>2026-05-12T05:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核物理観測量のモデル基づく外挿に対するベイズ的アプローチ（Bayesian approach to model-based extrapolation of nuclear observables）</news:title>
   <news:publication_date>2026-05-12T05:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689234</loc>
  <lastmod>2026-05-12T05:16:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い好奇心探索によるエージェント内探索（Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems）</news:title>
   <news:publication_date>2026-05-12T05:16:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689232</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>Wassersteinと価値認識型モデル学習の等価性（Equivalence Between Wasserstein and Value-Aware Loss for Model-based Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-12T04:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689230</loc>
  <lastmod>2026-05-12T04:23:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T04:23:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689228</loc>
  <lastmod>2026-05-12T04:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T04:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689226</loc>
  <lastmod>2026-05-12T04:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索の外部性とデータ多様性がもたらす効果（The Externalities of Exploration and How Data Diversity Helps Exploitation）</news:title>
   <news:publication_date>2026-05-12T04:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689224</loc>
  <lastmod>2026-05-12T04:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル近接勾配降下法による圧縮イメージング（Neural Proximal Gradient Descent for Compressive Imaging）</news:title>
   <news:publication_date>2026-05-12T04:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689222</loc>
  <lastmod>2026-05-12T04:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T04:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689220</loc>
  <lastmod>2026-05-12T04:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>追加知識を統合する高速でスケーラブルな共同推定器（A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models）</news:title>
   <news:publication_date>2026-05-12T04:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689218</loc>
  <lastmod>2026-05-12T03:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列因子化における収束保証付き加速（Provably convergent acceleration in factored gradient descent with applications in matrix sensing）</news:title>
   <news:publication_date>2026-05-12T03:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689216</loc>
  <lastmod>2026-05-12T03:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T03:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689214</loc>
  <lastmod>2026-05-12T03:30:55Z</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/689212</loc>
  <lastmod>2026-05-12T03:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T03:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689210</loc>
  <lastmod>2026-05-12T03:30:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTM学習の逆伝播を構造的に疎化して高速化する手法（Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training）</news:title>
   <news:publication_date>2026-05-12T03:30:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689208</loc>
  <lastmod>2026-05-12T03:30:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T03:30:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689206</loc>
  <lastmod>2026-05-12T03:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の雑音に強いDNN音声強調（DNN Based Speech Enhancement for Unseen Noises Using Monte Carlo Dropout）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689204</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/689202</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>人間の視線から学ぶ注意で視覚運動タスクを効率化する（AGIL: Learning Attention from Human for Visuomotor Tasks）</news:title>
   <news:publication_date>2026-05-12T02:38:35Z</news:publication_date>
   <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>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による材料物理の代替的枠組み（Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics）</news:title>
   <news:publication_date>2026-05-12T02:36:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689196</loc>
  <lastmod>2026-05-12T02:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット支援前立腺切除術における手術行動認識（Surgical Activity Recognition in Robot-Assisted Radical Prostatectomy using Deep Learning）</news:title>
   <news:publication_date>2026-05-12T02:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689194</loc>
  <lastmod>2026-05-12T02:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TRAPPIST-1系に対する深い電波上限（A Deep Radio Limit for the TRAPPIST-1 System）</news:title>
   <news:publication_date>2026-05-12T02:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689192</loc>
  <lastmod>2026-05-12T02:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的スペクトル密度に対する逆伝播（Backpropagation for Implicit Spectral Densities）</news:title>
   <news:publication_date>2026-05-12T02:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689190</loc>
  <lastmod>2026-05-12T01:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的合成分散削減勾配のサンプル効率改善（Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient）</news:title>
   <news:publication_date>2026-05-12T01:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689188</loc>
  <lastmod>2026-05-12T01:43:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入門天文学におけるLecture-Tutorialsの教育効果と実装指針（Lecture-Tutorials in Introductory Astronomy）</news:title>
   <news:publication_date>2026-05-12T01:43:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689186</loc>
  <lastmod>2026-05-12T01:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>純粋状態近似のための敵対的量子回路学習（Adversarial quantum circuit learning for pure state approximation）</news:title>
   <news:publication_date>2026-05-12T01:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689184</loc>
  <lastmod>2026-05-12T01:43:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対ネットワークを用いた分布の補正（Unfolding with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-12T01:43:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689182</loc>
  <lastmod>2026-05-12T01:42:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前景・背景分類による教師なし視覚表現学習（A Classification approach towards Unsupervised Learning of Visual Representations）</news:title>
   <news:publication_date>2026-05-12T01:42:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689180</loc>
  <lastmod>2026-05-12T01:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CIFAR-10分類器は本当に一般化しているのか（Do CIFAR-10 Classiﬁers Generalize to CIFAR-10?）</news:title>
   <news:publication_date>2026-05-12T01:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689178</loc>
  <lastmod>2026-05-12T01:41:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック空間における大余白分類（Large-Margin Classification in Hyperbolic Space）</news:title>
   <news:publication_date>2026-05-12T01:41:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689168</loc>
  <lastmod>2026-05-12T00:50:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kolmogorov方程式を深層学習で解く（Solving the Kolmogorov PDE by means of deep learning）</news:title>
   <news:publication_date>2026-05-12T00:50:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689166</loc>
  <lastmod>2026-05-12T00:49:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Whitening と Coloring によるバッチ正規化の拡張（WHITENING AND COLORING BATCH TRANSFORM FOR GANS）</news:title>
   <news:publication_date>2026-05-12T00:49:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689164</loc>
  <lastmod>2026-05-12T00:48:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械は耳を持つとよりよく聞こえる（Machines hear better when they have ears）</news:title>
   <news:publication_date>2026-05-12T00:48:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689162</loc>
  <lastmod>2026-05-12T00:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体系局在における相転移の特徴抽出の自動化（Automated discovery of characteristic features of phase transitions in many-body localization）</news:title>
   <news:publication_date>2026-05-12T00:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689160</loc>
  <lastmod>2026-05-12T00:47:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定なヘッシアン下でのニュートン法の全域線形収束（Global linear convergence of Newton’s method without strong-convexity or Lipschitz gradients）</news:title>
   <news:publication_date>2026-05-12T00:47:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689158</loc>
  <lastmod>2026-05-12T00:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴に適応するグラフと過分割グラフ（Adapted and Oversegmenting Graphs: Application to Geometric Deep Learning）</news:title>
   <news:publication_date>2026-05-12T00:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689156</loc>
  <lastmod>2026-05-12T00:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン探索型多次元尺度法（Pattern Search Multidimensional Scaling）</news:title>
   <news:publication_date>2026-05-12T00:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689154</loc>
  <lastmod>2026-05-11T23:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現の逆変換と自己回帰密度モデルによる解釈（Inverting Supervised Representations with Autoregressive Neural Density Models）</news:title>
   <news:publication_date>2026-05-11T23:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689152</loc>
  <lastmod>2026-05-11T23:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習で素子の信頼性問題を克服する（Overcoming device unreliability with continuous learning in a population coding based computing system）</news:title>
   <news:publication_date>2026-05-11T23:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689150</loc>
  <lastmod>2026-05-11T23:55:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波銀河形態の生成と解析（Radio Galaxy Morphology Generation Using DNN Autoencoder and Gaussian Mixture Models）</news:title>
   <news:publication_date>2026-05-11T23:55:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689148</loc>
  <lastmod>2026-05-11T23:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙インフレーションは究極の顕微鏡である（Cosmic Inflation: The Most Powerful Microscope in the Universe）</news:title>
   <news:publication_date>2026-05-11T23:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689146</loc>
  <lastmod>2026-05-11T23:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療分野における機械学習の課題と機会の総覧（A Review of Challenges and Opportunities in Machine Learning for Health）</news:title>
   <news:publication_date>2026-05-11T23:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689144</loc>
  <lastmod>2026-05-11T23:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーシステンス・パスとシグネチャ特徴量による位相データ解析（Persistence paths and signature features in topological data analysis）</news:title>
   <news:publication_date>2026-05-11T23:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689142</loc>
  <lastmod>2026-05-11T23:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN訓練の収束を加速する非線形手法の実践的意義（NONLINEAR ACCELERATION OF CNNS）</news:title>
   <news:publication_date>2026-05-11T23:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689140</loc>
  <lastmod>2026-05-11T23:02:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模顔認識のための高精度かつ高効率な類似検索（Accurate and Efficient Similarity Search for Large Scale Face Recognition）</news:title>
   <news:publication_date>2026-05-11T23:02:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689138</loc>
  <lastmod>2026-05-11T23:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線診断レポート品質の自動生成による説明可能なAIの道（Producing radiologist-quality reports for interpretable artificial intelligence）</news:title>
   <news:publication_date>2026-05-11T23:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689136</loc>
  <lastmod>2026-05-11T23:02:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRI臓器セグメンテーションのドメイン適応と逆分類精度（Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy）</news:title>
   <news:publication_date>2026-05-11T23:02:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689134</loc>
  <lastmod>2026-05-11T23:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ケプラー観測データにおけるフレア検出の機械学習的手法（Finding flares in Kepler data using machine-learning tools）</news:title>
   <news:publication_date>2026-05-11T23:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689132</loc>
  <lastmod>2026-05-11T23:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型圧縮アーティファクト除去の実践：深層残差ネットワークによるBPG後処理（Learned Compression Artifact Removal by Deep Residual Networks）</news:title>
   <news:publication_date>2026-05-11T23:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689130</loc>
  <lastmod>2026-05-11T23:01:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース盲復号における局所最適解の構造（Structured Local Optima in Sparse Blind Deconvolution）</news:title>
   <news:publication_date>2026-05-11T23:01:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689128</loc>
  <lastmod>2026-05-11T23:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチユーザーネットワークにおける情報鮮度最適化と強化学習の適用（A Reinforcement Learning Approach to Age of Information in Multi-User Networks）</news:title>
   <news:publication_date>2026-05-11T23:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689126</loc>
  <lastmod>2026-05-11T22:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分相関ハイパーサーフェスと有向ガウス型グラフィカルモデル（Partial Correlation Hypersurfaces in Gaussian Graphical Models）</news:title>
   <news:publication_date>2026-05-11T22:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689124</loc>
  <lastmod>2026-05-11T22:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存知識を活かして新しい解剖学と画像を学ぶ（Learn the new, keep the old: Extending pretrained models with new anatomy and images）</news:title>
   <news:publication_date>2026-05-11T22:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689122</loc>
  <lastmod>2026-05-11T22:09:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による凸境界を用いた線形二次制御方策合成（Learning convex bounds for linear quadratic control policy synthesis）</news:title>
   <news:publication_date>2026-05-11T22:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689120</loc>
  <lastmod>2026-05-11T22:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの自然言語生成（Natural Language Generation for Electronic Health Records）</news:title>
   <news:publication_date>2026-05-11T22:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689118</loc>
  <lastmod>2026-05-11T22:08:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Oblivious DNSによるDNS問い合わせのプライバシー確保（Oblivious DNS: Practical Privacy for DNS Queries）</news:title>
   <news:publication_date>2026-05-11T22:08:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689116</loc>
  <lastmod>2026-05-11T22:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>包括的ニューラルランダムフィールドによる生成モデリング（Generative Modeling by Inclusive Neural Random Fields）</news:title>
   <news:publication_date>2026-05-11T22:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689114</loc>
  <lastmod>2026-05-11T22:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一チャンネル音源分離のためのスパース探索と辞書学習（Sparse Pursuit and Dictionary Learning for Blind Source Separation in Polyphonic Music Recordings）</news:title>
   <news:publication_date>2026-05-11T22:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689112</loc>
  <lastmod>2026-05-11T21:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論を活用した強化学習によるクラウドソーシングのインセンティブ設計（Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing）</news:title>
   <news:publication_date>2026-05-11T21:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689110</loc>
  <lastmod>2026-05-11T21:08:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球状星団における中間質量ブラックホールの探査（THE MAVERIC SURVEY: STILL NO EVIDENCE FOR ACCRETING INTERMEDIATE-MASS BLACK HOLES IN GLOBULAR CLUSTERS）</news:title>
   <news:publication_date>2026-05-11T21:08:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689108</loc>
  <lastmod>2026-05-11T21:08:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二ブロック可分凸最適化問題に対する近接交互最小化アルゴリズム（The Proximal Alternating Minimization Algorithm for two-block separable convex optimization problems with linear constraints）</news:title>
   <news:publication_date>2026-05-11T21:08:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689106</loc>
  <lastmod>2026-05-11T21:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳におけるドメイン適応の総覧（A Survey of Domain Adaptation for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-11T21:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689104</loc>
  <lastmod>2026-05-11T21:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TAPASによる学習不要の精度予測（TAPAS: Train-less Accuracy Predictor for Architecture Search）</news:title>
   <news:publication_date>2026-05-11T21:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689102</loc>
  <lastmod>2026-05-11T21:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使った教師なし物体共ローカライゼーション（Generative Adversarial Networks for Unsupervised Object Co-localization）</news:title>
   <news:publication_date>2026-05-11T21:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689100</loc>
  <lastmod>2026-05-11T21:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書の分割と学習目標自動生成がもたらす授業設計の効率化（Document Chunking and Learning Objective Generation for Instruction Design）</news:title>
   <news:publication_date>2026-05-11T21:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689098</loc>
  <lastmod>2026-05-11T20:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不正確な近接オンライン勾配法による動的最適化の追跡（Online Learning with Inexact Proximal Online Gradient Descent Algorithms）</news:title>
   <news:publication_date>2026-05-11T20:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689096</loc>
  <lastmod>2026-05-11T20:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>問いへの好奇心を育てる――学習した注意機構によるノベルティ探索（Being curious about the answers to questions: novelty search with learned attention）</news:title>
   <news:publication_date>2026-05-11T20:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689094</loc>
  <lastmod>2026-05-11T20:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多車両フロッキング制御におけるDDPGの適用（Multi-vehicle Flocking Control with Deep Deterministic Policy Gradient Method）</news:title>
   <news:publication_date>2026-05-11T20:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689092</loc>
  <lastmod>2026-05-11T20:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチトラック楽曲の潜在空間学習（LEARNING A LATENT SPACE OF MULTITRACK MEASURES）</news:title>
   <news:publication_date>2026-05-11T20:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689090</loc>
  <lastmod>2026-05-11T20:12:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳のスケーリング（Scaling Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-11T20:12:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689088</loc>
  <lastmod>2026-05-11T20:12:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに強い顔認識表現学習（Deep Imbalanced Learning for Face Recognition and Attribute Prediction）</news:title>
   <news:publication_date>2026-05-11T20:12:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689086</loc>
  <lastmod>2026-05-11T20:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ記述技術の全体像と評価指標の課題（Video Description: A Survey of Methods, Datasets and Evaluation Metrics）</news:title>
   <news:publication_date>2026-05-11T20:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689084</loc>
  <lastmod>2026-05-11T19:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間-スペクトル深層残差ネットワークによる高スペクトル画像のノイズ除去（Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-11T19:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689082</loc>
  <lastmod>2026-05-11T19:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形係数による深層ニューラルネットワークの一般化予測（The Nonlinearity Coefficient: Predicting Generalization in Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-11T19:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689080</loc>
  <lastmod>2026-05-11T19:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化の理解（Understanding Batch Normalization）</news:title>
   <news:publication_date>2026-05-11T19:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689078</loc>
  <lastmod>2026-05-11T19:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタリーブド低ランクグループ畳み込み（IGCV3: Interleaved Low-Rank Group Convolutions）</news:title>
   <news:publication_date>2026-05-11T19:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689076</loc>
  <lastmod>2026-05-11T19:19:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抵抗性クロスポイント素子によるLSTM学習の高速化（Training LSTM Networks with Resistive Cross-Point Devices）</news:title>
   <news:publication_date>2026-05-11T19:19:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689074</loc>
  <lastmod>2026-05-11T19:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>簡略モデルと概ね楽観的計画による高速探索（FAST EXPLORATION WITH SIMPLIFIED MODELS AND APPROXIMATELY OPTIMISTIC PLANNING IN MODEL-BASED REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-05-11T19:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689072</loc>
  <lastmod>2026-05-11T19:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非微分モデルの再パラメータ化勾配（Reparameterization Gradient for Non-differentiable Models）</news:title>
   <news:publication_date>2026-05-11T19:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689070</loc>
  <lastmod>2026-05-11T18:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル制御変量によるモンテカルロ分散削減（Neural Control Variates for Monte Carlo Variance Reduction）</news:title>
   <news:publication_date>2026-05-11T18:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689068</loc>
  <lastmod>2026-05-11T18:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーチ駆動で表現豊かなリップ同期を実現する条件付き逐次生成対抗ネットワーク（Speech-Driven Expressive Talking Lips with Conditional Sequential Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-11T18:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689066</loc>
  <lastmod>2026-05-11T18:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深くネストされた階層モデルの高速推定（Fitting a Deeply-Nested Hierarchical Model to a Large Book Review Dataset Using a Moment-Based Estimator）</news:title>
   <news:publication_date>2026-05-11T18:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689064</loc>
  <lastmod>2026-05-11T18:26:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンデムブロックによる畳み込みニューラルネットワークの再考（Tandem Blocks in Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-11T18:26:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689062</loc>
  <lastmod>2026-05-11T18:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照スキャン不要なEPIゴースト補正のk-空間ディープラーニング（k-Space Deep Learning for Reference-free EPI Ghost Correction）</news:title>
   <news:publication_date>2026-05-11T18:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689060</loc>
  <lastmod>2026-05-11T18:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ジャクソン微分に基づくq-ニューロン（q-Neurons: Neuron Activations based on Stochastic Jackson’s Derivative Operators）</news:title>
   <news:publication_date>2026-05-11T18:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689058</loc>
  <lastmod>2026-05-11T18:25:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の解釈は投影図である（Interpreting Deep Learning: The Machine Learning Rorschach Test?）</news:title>
   <news:publication_date>2026-05-11T18:25:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689056</loc>
  <lastmod>2026-05-11T17:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>まれな危険状況に対する予防行動の模倣学習（Modeling Preemptive Behaviors for Uncommon Hazardous Situations From Demonstrations）</news:title>
   <news:publication_date>2026-05-11T17:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689054</loc>
  <lastmod>2026-05-11T17:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海面水温の予測と再構築におけるパッチレベルニューラルネットワーク表現（SEA SURFACE TEMPERATURE PREDICTION AND RECONSTRUCTION USING PATCH-LEVEL NEURAL NETWORK REPRESENTATIONS）</news:title>
   <news:publication_date>2026-05-11T17:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689052</loc>
  <lastmod>2026-05-11T17:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレベル3D CNNによるマルチスケール空間特徴学習（Multi-level 3D CNN for Learning Multi-scale Spatial Features）</news:title>
   <news:publication_date>2026-05-11T17:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689050</loc>
  <lastmod>2026-05-11T17:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコア環境における並列多重配列アラインメントアルゴリズムの現状調査（A Survey of the State-of-the-Art Parallel Multiple Sequence Alignment Algorithms on Multicore Systems）</news:title>
   <news:publication_date>2026-05-11T17:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689048</loc>
  <lastmod>2026-05-11T17:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模シーンにおける光フローを用いた新規ビデオ予測（Novel Video Prediction for Large-scale Scene using Optical Flow）</news:title>
   <news:publication_date>2026-05-11T17:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689046</loc>
  <lastmod>2026-05-11T17:31:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロンの重要度はどのように測るか（How Important Is a Neuron?）</news:title>
   <news:publication_date>2026-05-11T17:31:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689044</loc>
  <lastmod>2026-05-11T17:31:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-11T17:31:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689042</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>個人のゲノムを大規模に分類・推定する畳み込み埋め込みネットワーク（Convolutional Embedded Networks for Population Scale Clustering and Bio-ancestry Inferencing）</news:title>
   <news:publication_date>2026-05-11T16:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-11T16:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン編集による外挿可能な変換学習（Out-of-Sample Extrapolation with Neuron Editing）</news:title>
   <news:publication_date>2026-05-11T16:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689036</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>2026-05-11T16:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689034</loc>
  <lastmod>2026-05-11T16:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Segment Hash Learning for Music Generation（Deep Segment Hash Learning for Music Generation）</news:title>
   <news:publication_date>2026-05-11T16:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689032</loc>
  <lastmod>2026-05-11T16:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fine-Pruningによるバックドア攻撃防御（Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-11T16:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689030</loc>
  <lastmod>2026-05-11T16:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな画像変換に対する深層畳み込みネットワークの一般化の脆弱性（Why do deep convolutional networks generalize so poorly to small image transformations?）</news:title>
   <news:publication_date>2026-05-11T16:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689028</loc>
  <lastmod>2026-05-11T15:44:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対応データから学ぶ動画要約（Video Summarization by Learning from Unpaired Data）</news:title>
   <news:publication_date>2026-05-11T15:44:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689026</loc>
  <lastmod>2026-05-11T15:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムスカラー化による柔軟な多目的ベイズ最適化フレームワーク（A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations）</news:title>
   <news:publication_date>2026-05-11T15:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689024</loc>
  <lastmod>2026-05-11T15:44:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における血縁検証のための教師付き混合ノルムオートエンコーダ（Supervised Mixed Norm Autoencoder for Kinship Verification in Unconstrained Videos）</news:title>
   <news:publication_date>2026-05-11T15:44:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689022</loc>
  <lastmod>2026-05-11T15:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-11T15:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689020</loc>
  <lastmod>2026-05-11T15:42:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健性は精度と相容れないことがある（Robustness May Be at Odds with Accuracy）</news:title>
   <news:publication_date>2026-05-11T15:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689018</loc>
  <lastmod>2026-05-11T15:42:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>What the Vec?：確率的根拠に基づく埋め込みの理解（What the Vec? Towards Probabilistically Grounded Embeddings）</news:title>
   <news:publication_date>2026-05-11T15:42:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689016</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>機械学習によるバウンス作用量計算の単純化（Machine learning for bounce calculation）</news:title>
   <news:publication_date>2026-05-11T15:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689014</loc>
  <lastmod>2026-05-11T14:50:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M51銀河系における広帯域X線分光解析の要点（Broadband X-ray spectral analysis of the M51 system）</news:title>
   <news:publication_date>2026-05-11T14:50:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689012</loc>
  <lastmod>2026-05-11T14:49:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で探る多体局在：つかめない非エルゴード金属を追う (Machine learning many-body localization: Search for the elusive nonergodic metal)</news:title>
   <news:publication_date>2026-05-11T14:49:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689010</loc>
  <lastmod>2026-05-11T14:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合意（コンセンサス）と最適性のトレードオフに関する研究（On Consensus-Optimality Trade-offs in Collaborative Deep Learning）</news:title>
   <news:publication_date>2026-05-11T14:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689008</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>マイクロレベルのメタラーニングによる推薦アルゴリズム選択（One-at-a-time: A Meta-Learning Recommender-System for Recommendation-Algorithm Selection on Micro Level）</news:title>
   <news:publication_date>2026-05-11T14:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689006</loc>
  <lastmod>2026-05-11T14:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない試行で学ぶ深層強化学習（Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models）</news:title>
   <news:publication_date>2026-05-11T14:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689004</loc>
  <lastmod>2026-05-11T14:47:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MPDCompressによるニューラルネット圧縮（MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689002</loc>
  <lastmod>2026-05-11T14:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PID2018 ベンチマークにおける学習フィードフォワード制御（PID2018 Benchmark Challenge: learning feedforward control）</news:title>
   <news:publication_date>2026-05-11T14:47:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689000</loc>
  <lastmod>2026-05-11T13:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CuisineNetに基づく食の属性分類（CuisineNet: Food Attributes Classification using Multi-scale Convolution Network）</news:title>
   <news:publication_date>2026-05-11T13:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688998</loc>
  <lastmod>2026-05-11T13:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化が汎化に果たす役割の理解に向けて (Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks)</news:title>
   <news:publication_date>2026-05-11T13:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688996</loc>
  <lastmod>2026-05-11T13:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文認識を用いたマルチタスク学習によるコードスイッチ言語モデリング (Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning)</news:title>
   <news:publication_date>2026-05-11T13:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688994</loc>
  <lastmod>2026-05-11T13:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-11T13:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688992</loc>
  <lastmod>2026-05-11T13:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓拡散テンソルMRIの確率的深層圧縮センシング（Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI）</news:title>
   <news:publication_date>2026-05-11T13:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688990</loc>
  <lastmod>2026-05-11T13:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-11T13:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688988</loc>
  <lastmod>2026-05-11T13:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-11T13:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688986</loc>
  <lastmod>2026-05-11T12:52:48Z</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/688984</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>適応システム同定におけるLMSと進化計算の統合（Adaptive System Identification Using LMS Algorithm Integrated with Evolutionary Computation）</news:title>
   <news:publication_date>2026-05-11T12:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688982</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>クエリ時に段階的にデータを強化するPIQUE（PIQUE: Progressive Integrated QUery Operator with Pay-As-You-Go Enrichment）</news:title>
   <news:publication_date>2026-05-11T12:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688980</loc>
  <lastmod>2026-05-11T12:51:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア製品ラインにおける敵対的構成への接近（Towards Adversarial Configurations for Software Product Lines）</news:title>
   <news:publication_date>2026-05-11T12:51:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688978</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: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>
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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>プライバシー配慮型の深層ニューラルネットワークのオフロード（Privacy Aware Offloading of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-11T12:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688972</loc>
  <lastmod>2026-05-11T11:59:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ClaRANによる電波源自動分類（Classifying Radio sources Automatically with Neural networks）</news:title>
   <news:publication_date>2026-05-11T11:59:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688970</loc>
  <lastmod>2026-05-11T11:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>私の分類器はなぜ差別的か？（Why Is My Classifier Discriminatory?）</news:title>
   <news:publication_date>2026-05-11T11:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688968</loc>
  <lastmod>2026-05-11T11:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照なしセンサ較正がもたらす現場の変革（Reference-free Calibration in Sensor Networks）</news:title>
   <news:publication_date>2026-05-11T11:58:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688966</loc>
  <lastmod>2026-05-11T11:57:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MolGANによる分子グラフ生成の効率化（MolGAN: An implicit generative model for small molecular graphs）</news:title>
   <news:publication_date>2026-05-11T11:57:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688964</loc>
  <lastmod>2026-05-11T11:57:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RBFネットワークの耐故障・中心選択におけるl0ノルム最適化（l0-norm Based Algorithm for Training Fault Tolerant RBF Networks and Selecting Centers）</news:title>
   <news:publication_date>2026-05-11T11:57:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688962</loc>
  <lastmod>2026-05-11T11:57:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>望ましい機能性を持つ物体形状の自動生成（AUTOMATIC GENERATION OF OBJECT SHAPES WITH DESIRED FUNCTIONALITIES）</news:title>
   <news:publication_date>2026-05-11T11:57:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688960</loc>
  <lastmod>2026-05-11T11:56:49Z</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を用いた大規模横断歩道データ取得と分類の自動化（Automatic Large-Scale Data Acquisition via Crowdsourcing for Crosswalk Classification: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-11T11:56:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688958</loc>
  <lastmod>2026-05-11T11:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像集合分類における複数多様体計量学習の要点 (Multiple Manifolds Metric Learning with Application to Image Set Classification)</news:title>
   <news:publication_date>2026-05-11T11:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688956</loc>
  <lastmod>2026-05-11T10:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層残差ネットワークによる翌日電力負荷予測（Day-Ahead Load Forecasting Based on Deep Residual Networks）</news:title>
   <news:publication_date>2026-05-11T10:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688954</loc>
  <lastmod>2026-05-11T10:56:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速なL1最小化アルゴリズムによるスパース近似の実用化（Fast L1-Minimization Algorithm for Sparse Approximation Based on an Improved LPNN-LCA framework）</news:title>
   <news:publication_date>2026-05-11T10:56:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688952</loc>
  <lastmod>2026-05-11T10:55:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の深度マップ生成を学習する（Learning to Generate Facial Depth Maps）</news:title>
   <news:publication_date>2026-05-11T10:55:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688950</loc>
  <lastmod>2026-05-11T10:55:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングポリマ分子動力学と能動学習を用いた熱反応速度係数の自動計算（Automated Calculation of Thermal Rate Coefﬁcients using Ring Polymer Molecular Dynamics and Machine-Learning Interatomic Potentials with Active Learning）</news:title>
   <news:publication_date>2026-05-11T10:55:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688948</loc>
  <lastmod>2026-05-11T10:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スカラー・ベクトル・テンソル理論によるダークエネルギーの新展開（Dark energy in scalar-vector-tensor theories）</news:title>
   <news:publication_date>2026-05-11T10:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688946</loc>
  <lastmod>2026-05-11T10:54:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名ウォーク埋め込み（Anonymous Walk Embeddings）</news:title>
   <news:publication_date>2026-05-11T10:54:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688944</loc>
  <lastmod>2026-05-11T10:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習のダイナミクス：ランダム行列アプローチ (The Dynamics of Learning: A Random Matrix Approach)</news:title>
   <news:publication_date>2026-05-11T10:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688942</loc>
  <lastmod>2026-05-11T10:02:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データにおけるランダム特徴写像のスペクトル解析（On the Spectrum of Random Features Maps of High Dimensional Data）</news:title>
   <news:publication_date>2026-05-11T10:02:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688940</loc>
  <lastmod>2026-05-11T10:02:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースデータ回帰のための信頼度伝播を行うCNN（Propagating Confidences through CNNs for Sparse Data Regression）</news:title>
   <news:publication_date>2026-05-11T10:02:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688938</loc>
  <lastmod>2026-05-11T10:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習におけるワッサースタイン距離とSinkhorn近似の微分特性 (Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance)</news:title>
   <news:publication_date>2026-05-11T10:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688936</loc>
  <lastmod>2026-05-11T10:01:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズネット構造学習の精度と速度（Who Learns Better Bayesian Network Structures: Accuracy and Speed of Structure Learning Algorithms）</news:title>
   <news:publication_date>2026-05-11T10:01:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688934</loc>
  <lastmod>2026-05-11T10:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCTファイバとconvGRU-CNNを用いたニードル先端力推定（Needle Tip Force Estimation using an OCT Fiber and a Fused convGRU-CNN Architecture）</news:title>
   <news:publication_date>2026-05-11T10:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688932</loc>
  <lastmod>2026-05-11T10:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Al-Mg-Si(-Cu)合金の析出物位相進化の解明（The evolution of precipitate crystal structures in an Al-Mg-Si(-Cu) alloy）</news:title>
   <news:publication_date>2026-05-11T10:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688930</loc>
  <lastmod>2026-05-11T09:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散コンピューティングの予測性能モデリング（Predictive Performance Modeling for Distributed Computing using Black-Box Monitoring and Machine Learning）</news:title>
   <news:publication_date>2026-05-11T09:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688928</loc>
  <lastmod>2026-05-11T09:08:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピノールボース気体における非平衡普遍ダイナミクスの観測（Observation of universal dynamics in a spinor Bose gas far from equilibrium）</news:title>
   <news:publication_date>2026-05-11T09:08:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688926</loc>
  <lastmod>2026-05-11T09:07:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語-ヒンディー混合コードのスタンス検出コーパス（An English-Hindi Code-Mixed Corpus: Stance Annotation and Baseline System）</news:title>
   <news:publication_date>2026-05-11T09:07:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688924</loc>
  <lastmod>2026-05-11T09:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Foresee: カオスな道路環境の予測とオンライン学習（Foresee: Attentive Future Projections of Chaotic Road Environments with Online Training）</news:title>
   <news:publication_date>2026-05-11T09:06:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688922</loc>
  <lastmod>2026-05-11T09:05:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づく移動予測で実現するインテリジェント二重接続（Deep Learning-based Intelligent Dual Connectivity for Mobility Management in Dense Network）</news:title>
   <news:publication_date>2026-05-11T09:05:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688920</loc>
  <lastmod>2026-05-11T09:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に対する敵対的攻撃と防御のインタラクティブ実験プラットフォーム（ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio）</news:title>
   <news:publication_date>2026-05-11T09:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688918</loc>
  <lastmod>2026-05-11T09:05:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未確認ロボット検出と関節推定のための転移学習（Transfer Learning for Unseen Robot Detection and Joint Estimation on a Multi-Objective Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-11T09:05:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688916</loc>
  <lastmod>2026-05-11T08:12:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多くの行動を持つThompson Samplingの情報理論的解析（An Information-Theoretic Analysis for Thompson Sampling with Many Actions）</news:title>
   <news:publication_date>2026-05-11T08:12:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688914</loc>
  <lastmod>2026-05-11T08:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Factorization Machine による Android マルウェア検出（Android Malware Detection based on Factorization Machine）</news:title>
   <news:publication_date>2026-05-11T08:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688912</loc>
  <lastmod>2026-05-11T08:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序付けられたラベルの分類を改善する同時多課題学習（Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels）</news:title>
   <news:publication_date>2026-05-11T08:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688910</loc>
  <lastmod>2026-05-11T08:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窓越しの反射を同時に除去する多スケールネットワーク（CRRN: Multi-Scale Guided Concurrent Reflection Removal Network）</news:title>
   <news:publication_date>2026-05-11T08:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688908</loc>
  <lastmod>2026-05-11T08:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的照応表現認識の実態：モデルは何を学んでいるのか（Visual Referring Expression Recognition: What Do Systems Actually Learn?）</news:title>
   <news:publication_date>2026-05-11T08:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688906</loc>
  <lastmod>2026-05-11T08:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力凸ニューラルネットワークを用いた最適制御（Optimal Control Via Neural Networks: A Convex Approach）</news:title>
   <news:publication_date>2026-05-11T08:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688904</loc>
  <lastmod>2026-05-11T08:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ゼロ次最適化の分散削減法（Stochastic Zeroth-order Optimization via Variance Reduction method）</news:title>
   <news:publication_date>2026-05-11T08:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688902</loc>
  <lastmod>2026-05-11T07:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ内で動くLSTM――抵抗メモリクロスバー上の長短期記憶ネットワーク（Long short-term memory networks in memristor crossbars）</news:title>
   <news:publication_date>2026-05-11T07:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688900</loc>
  <lastmod>2026-05-11T07:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlchemistによるSparkからの高性能計算オフロード（Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist）</news:title>
   <news:publication_date>2026-05-11T07:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688898</loc>
  <lastmod>2026-05-11T07:19:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>命題論理の自動証明合成に深層ニューラルネットワークを適用する研究（Automated proof synthesis for propositional logic with deep neural networks）</news:title>
   <news:publication_date>2026-05-11T07:19:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688896</loc>
  <lastmod>2026-05-11T07:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由空間におけるプラズモニクスの再考—超振動場で観測される巨大波数、渦、エネルギー逆流（“Plasmonics” in free space: observation of giant wavevectors, vortices and energy backflow in superoscillatory optical fields）</news:title>
   <news:publication_date>2026-05-11T07:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688894</loc>
  <lastmod>2026-05-11T07:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無限アーム・バンディットの最適性を導く確信境界（INFINITE ARMS BANDIT: OPTIMALITY VIA CONFIDENCE BOUNDS）</news:title>
   <news:publication_date>2026-05-11T07:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688892</loc>
  <lastmod>2026-05-11T07:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成長と剪定で実現するコンパクトで高速かつ高精度なLSTM（Grow and Prune Compact, Fast, and Accurate LSTMs）</news:title>
   <news:publication_date>2026-05-11T07:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688890</loc>
  <lastmod>2026-05-11T07:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元ベイズ最適化に関する厳密な後悔境界の示唆（Tight Regret Bounds for Bayesian Optimization in One Dimension）</news:title>
   <news:publication_date>2026-05-11T07:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688888</loc>
  <lastmod>2026-05-11T06:26:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3次元骨格データに対する細部から粗へ導く畳み込みネットワーク（A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition）</news:title>
   <news:publication_date>2026-05-11T06:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688886</loc>
  <lastmod>2026-05-11T06:26:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像と転移学習を用いた一倍体トウモロコシ種子の識別（Hyperspectral Imaging Technology and Transfer Learning Utilized in Identification Haploid Maize Seeds）</news:title>
   <news:publication_date>2026-05-11T06:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688884</loc>
  <lastmod>2026-05-11T06:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>間隙水素がSrCoO2.5反強磁性絶縁体に果たす役割（The role of interstitial hydrogen in SrCoO2.5 antiferromagnetic insulator）</news:title>
   <news:publication_date>2026-05-11T06:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688882</loc>
  <lastmod>2026-05-11T06:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数活性化関数を用いる畳み込みニューラルネットワークの可能性（Multi-function Convolutional Neural Networks for Improving Image Classification Performance）</news:title>
   <news:publication_date>2026-05-11T06:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688880</loc>
  <lastmod>2026-05-11T06:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像のドメインランダマイゼーションとGANによる精緻化で実現する実世界物体検出（Object Detection using Domain Randomization and Generative Adversarial Refinement of Synthetic Images）</news:title>
   <news:publication_date>2026-05-11T06:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688878</loc>
  <lastmod>2026-05-11T06:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoZOOMによる黒箱ニューラルネット攻撃の効率化（AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks）</news:title>
   <news:publication_date>2026-05-11T06:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688876</loc>
  <lastmod>2026-05-11T06:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分で高速に算出するグラフのフォン・ノイマンエントロピー（Fast Incremental von Neumann Graph Entropy Computation）</news:title>
   <news:publication_date>2026-05-11T06:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688874</loc>
  <lastmod>2026-05-11T05:33:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似的なLTLモデル検査と機械学習による加速（Approximate LTL Model Checking）</news:title>
   <news:publication_date>2026-05-11T05:33:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688872</loc>
  <lastmod>2026-05-11T05:33:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型タスク指向モデルに対する敵対的学習（Adversarial Learning of Task-Oriented Neural Dialog Models）</news:title>
   <news:publication_date>2026-05-11T05:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688870</loc>
  <lastmod>2026-05-11T05:33:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共学習による深層ニューラルネットワークの改良（Collaborative Learning for Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-11T05:33:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688868</loc>
  <lastmod>2026-05-11T05:32:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スーパーセグメント強化型ペアワイズCRFによるセマンティックセグメンテーションの実践的改善（SUPERPIXEL-ENHANCED PAIRWISE CONDITIONAL RANDOM FIELD FOR SEMANTIC SEGMENTATION）</news:title>
   <news:publication_date>2026-05-11T05:32:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688866</loc>
  <lastmod>2026-05-11T05:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な検定法と実験豊富レジーム（Optimal Testing in the Experiment-rich Regime）</news:title>
   <news:publication_date>2026-05-11T05:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688864</loc>
  <lastmod>2026-05-11T05:32:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデルを識別器とする教師なしテキストスタイル転換（Unsupervised Text Style Transfer using Language Models as Discriminators）</news:title>
   <news:publication_date>2026-05-11T05:32:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688862</loc>
  <lastmod>2026-05-11T05:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数式の不変表現の構築（Invariant Representation of Mathematical Expressions）</news:title>
   <news:publication_date>2026-05-11T05:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688860</loc>
  <lastmod>2026-05-11T04:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深海における可混合流体の非線形内部孤立波の実験的研究（Experimental investigation of nonlinear internal waves in deep water with miscible fluids）</news:title>
   <news:publication_date>2026-05-11T04:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688858</loc>
  <lastmod>2026-05-11T04:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モダリティを賢く組み合わせる学習法（Learn to Combine Modalities in Multimodal Deep Learning）</news:title>
   <news:publication_date>2026-05-11T04:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688856</loc>
  <lastmod>2026-05-11T04:39:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフ伝播を再考したゼロショット学習（Rethinking Knowledge Graph Propagation for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-05-11T04:39:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688854</loc>
  <lastmod>2026-05-11T04:38:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムメッシュ射影による逆問題の安定化（Random Mesh Projectors for Inverse Problems）</news:title>
   <news:publication_date>2026-05-11T04:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688852</loc>
  <lastmod>2026-05-11T04:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層クラスタリングのための新しいマルチクラスタリング手法（A Novel Multi-clustering Method for Hierarchical Clusterings, Based on Boosting）</news:title>
   <news:publication_date>2026-05-11T04:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688850</loc>
  <lastmod>2026-05-11T04:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さと非線形性が生む暗黙の探索（Depth and nonlinearity induce implicit exploration for RL）</news:title>
   <news:publication_date>2026-05-11T04:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688848</loc>
  <lastmod>2026-05-11T04:38:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ビデオポートレートの革命（Deep Video Portraits）</news:title>
   <news:publication_date>2026-05-11T04:38:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688846</loc>
  <lastmod>2026-05-11T03:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層意味表現アーキテクチャと識別的特徴可視化による神経画像解析（Deep Semantic Architecture with discriminative feature visualization for neuroimage analysis）</news:title>
   <news:publication_date>2026-05-11T03:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688844</loc>
  <lastmod>2026-05-11T03:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師付きポリシー更新（Supervised Policy Update）による効率的な強化学習</news:title>
   <news:publication_date>2026-05-11T03:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688842</loc>
  <lastmod>2026-05-11T03:44:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次学習における能動的かつ適応的な枠組み（Active and Adaptive Sequential learning）</news:title>
   <news:publication_date>2026-05-11T03:44:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688840</loc>
  <lastmod>2026-05-11T03:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>繰り返し提示価格オークションの新しいメカニズム（NEW MECHANISM FOR REPEATED POSTED PRICE AUCTION WITHOUT DISCOUNTING）</news:title>
   <news:publication_date>2026-05-11T03:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688838</loc>
  <lastmod>2026-05-11T03:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全文文章のリップリーディングは可能か（Can DNNs Learn to Lipread Full Sentences?）</news:title>
   <news:publication_date>2026-05-11T03:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688836</loc>
  <lastmod>2026-05-11T03:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントに基づく変分逆制御（Variational Inverse Control with Events）</news:title>
   <news:publication_date>2026-05-11T03:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688834</loc>
  <lastmod>2026-05-11T03:43:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネルゲーティングによる動的経路選択（Channel Gating Neural Networks）</news:title>
   <news:publication_date>2026-05-11T03:43:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688832</loc>
  <lastmod>2026-05-11T02:51:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローレンツ対称性の違反と電子イオンコライダー（Lorentz violation and the electron-ion collider）</news:title>
   <news:publication_date>2026-05-11T02:51:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688830</loc>
  <lastmod>2026-05-11T02:51:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V341 Araeの分光学的研究（Spectroscopy of V341 Arae: A Nearby Nova-like Variable inside a Bow-Shock Nebula）</news:title>
   <news:publication_date>2026-05-11T02:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688828</loc>
  <lastmod>2026-05-11T02:50:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定のための説明を教える（Teaching Meaningful Explanations）</news:title>
   <news:publication_date>2026-05-11T02:50:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688826</loc>
  <lastmod>2026-05-11T02:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ディリクレ過程を用いた確率的軌跡分割（Probabilistic Trajectory Segmentation by Means of Hierarchical Dirichlet Process Switching Linear Dynamical Systems）</news:title>
   <news:publication_date>2026-05-11T02:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688824</loc>
  <lastmod>2026-05-11T02:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMは言語データの属性を利用する（LSTMs Exploit Linguistic Attributes of Data）</news:title>
   <news:publication_date>2026-05-11T02:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688822</loc>
  <lastmod>2026-05-11T02:48:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子衝突データのイメージ化による事象分類（Imaging particle collision data for event classification using machine learning）</news:title>
   <news:publication_date>2026-05-11T02:48:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688820</loc>
  <lastmod>2026-05-11T02:48:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統一的粒子最適化フレームワークによるスケーラブルなベイズサンプリング（A Unified Particle-Optimization Framework for Scalable Bayesian Sampling）</news:title>
   <news:publication_date>2026-05-11T02:48:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688818</loc>
  <lastmod>2026-05-11T01:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K-Beam Minimaxによる効率的な最適化（K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning）</news:title>
   <news:publication_date>2026-05-11T01:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688816</loc>
  <lastmod>2026-05-11T01:56:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ロバストスパース回帰（High Dimensional Robust Sparse Regression）</news:title>
   <news:publication_date>2026-05-11T01:56:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688814</loc>
  <lastmod>2026-05-11T01:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期における二峰性Lyα放射の確認（Confirmation of double peaked Lyα emission at z = 6.593）</news:title>
   <news:publication_date>2026-05-11T01:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688812</loc>
  <lastmod>2026-05-11T01:54:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Batch Normalization が最適化を助ける仕組み（How Does Batch Normalization Help Optimization?）</news:title>
   <news:publication_date>2026-05-11T01:54:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688810</loc>
  <lastmod>2026-05-11T01:54:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力変換によるドメイン適応のためのAdapterNet（AdapterNet - learning input transformation for domain adaptation）</news:title>
   <news:publication_date>2026-05-11T01:54:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688808</loc>
  <lastmod>2026-05-11T01:54:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒント対散漫：知能ティュータにおける“適切な助け”の探求（Hints vs Distractions in Intelligent Tutoring Systems: In search of the proper type of help）</news:title>
   <news:publication_date>2026-05-11T01:54:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688806</loc>
  <lastmod>2026-05-11T01:53:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権情報で不確実性を制御する深層学習（Deep Learning under Privileged Information Using Heteroscedastic Dropout）</news:title>
   <news:publication_date>2026-05-11T01:53:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688803</loc>
  <lastmod>2026-05-11T01:01:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的摂動に対する深層学習の安定性解析（Adversarial Noise Attacks of Deep Learning Architectures – Stability Analysis via Sparse-Modeled Signals）</news:title>
   <news:publication_date>2026-05-11T01:01:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688801</loc>
  <lastmod>2026-05-11T01:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariで一貫した性能を達成する手法（Observe and Look Further: Achieving Consistent Performance on Atari）</news:title>
   <news:publication_date>2026-05-11T01:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688799</loc>
  <lastmod>2026-05-11T01:00:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構成間の掃引体積を予測する深層ニューラルネットワーク（Deep Neural Networks for Swept Volume Prediction Between Configurations）</news:title>
   <news:publication_date>2026-05-11T01:00:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688797</loc>
  <lastmod>2026-05-11T00:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題に対する敵対的正則化の導入（Adversarial Regularizers in Inverse Problems）</news:title>
   <news:publication_date>2026-05-11T00:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688795</loc>
  <lastmod>2026-05-11T00:59:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTubeを見て難しい探索ゲームを攻略する方法（Playing hard exploration games by watching YouTube）</news:title>
   <news:publication_date>2026-05-11T00:59:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688793</loc>
  <lastmod>2026-05-11T00:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所発作の発作予測にCNNを用いる研究（Focal onset seizure prediction using convolutional networks）</news:title>
   <news:publication_date>2026-05-11T00:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688791</loc>
  <lastmod>2026-05-11T00:58:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの反射除去のための最適化手法（Mirror, Mirror, on the Wall: A Tailored Approach to Single Image Reflection Removal）</news:title>
   <news:publication_date>2026-05-11T00:58:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688789</loc>
  <lastmod>2026-05-11T00:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPA、Grit、Layoff予測の勝者モデル（Winning Models for GPA, Grit, and Layoff in the Fragile Families Challenge）</news:title>
   <news:publication_date>2026-05-11T00:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688787</loc>
  <lastmod>2026-05-11T00:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間を巻き込む解釈可能性事前分布（Human-in-the-Loop Interpretability Prior）</news:title>
   <news:publication_date>2026-05-11T00:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688785</loc>
  <lastmod>2026-05-11T00:05:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMD GANの勾配正則化が変えたもの（On gradient regularizers for MMD GANs）</news:title>
   <news:publication_date>2026-05-11T00:05:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688783</loc>
  <lastmod>2026-05-11T00:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前向き均一化推論による尤度不要の変分周辺化（Forward Amortized Inference for Likelihood-Free Variational Marginalization）</news:title>
   <news:publication_date>2026-05-11T00:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688781</loc>
  <lastmod>2026-05-11T00:04:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽い教師あり表現学習とグローバル可視化（Lightly-supervised Representation Learning with Global Interpretability）</news:title>
   <news:publication_date>2026-05-11T00:04:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688779</loc>
  <lastmod>2026-05-11T00:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳児のように学ぶ言語モデル——視覚情報で強化するニューラル言語獲得（Like a Baby: Visually Situated Neural Language Acquisition）</news:title>
   <news:publication_date>2026-05-11T00:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688777</loc>
  <lastmod>2026-05-11T00:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下でのオフポリシー学習を可能にしたActor Search Tree Critic（The Actor Search Tree Critic (ASTC) for Off-Policy POMDP Learning in Medical Decision Making）</news:title>
   <news:publication_date>2026-05-11T00:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688775</loc>
  <lastmod>2026-05-10T23:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子固体の化学シフトを機械学習で予測する（Chemical Shifts in Molecular Solids by Machine Learning）</news:title>
   <news:publication_date>2026-05-10T23:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688773</loc>
  <lastmod>2026-05-10T23:11:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多コア時代の疎行列ベクトル積最適化（Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures）</news:title>
   <news:publication_date>2026-05-10T23:11:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688771</loc>
  <lastmod>2026-05-10T23:10:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カップルを見つける深層学習――COUPLENETによる関係推薦（COUPLENET: Paying Attention to Couples with Coupled Attention for Relationship Recommendation）</news:title>
   <news:publication_date>2026-05-10T23:10:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688769</loc>
  <lastmod>2026-05-10T23:09:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>耳で譜面化を学ぶ──強化学習による多声音楽の自動書き起こし（LEARNING TO TRANSCRIBE BY EAR）</news:title>
   <news:publication_date>2026-05-10T23:09:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688767</loc>
  <lastmod>2026-05-10T23:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空気汚染予測を容易にするRパッケージairpred（airpred: A Flexible R Package Implementing Methods for Predicting Air Pollution）</news:title>
   <news:publication_date>2026-05-10T23:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688765</loc>
  <lastmod>2026-05-10T23:09:30Z</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支援復号による物理層ネットワーク符号化ランダムアクセス（Neural Network Aided Decoding for Physical-Layer Network Coding Random Access）</news:title>
   <news:publication_date>2026-05-10T23:09:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688763</loc>
  <lastmod>2026-05-10T23:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低解像度顔認識の現場対応（On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques）</news:title>
   <news:publication_date>2026-05-10T23:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688761</loc>
  <lastmod>2026-05-10T22:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MDS-UPDRSと機械学習によるパーキンソン病ステージ推定の改良（Novel and Improved Stage Estimation in Parkinson&amp;#039;s Disease using Clinical Scales and Machine Learning）</news:title>
   <news:publication_date>2026-05-10T22:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688759</loc>
  <lastmod>2026-05-10T22:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低品質画像における顔認識の総覧（Face Recognition in Low Quality Images: A Survey）</news:title>
   <news:publication_date>2026-05-10T22:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688757</loc>
  <lastmod>2026-05-10T22:16:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全なラベルで学ぶ識別器の強さと限界（Classification with imperfect training labels）</news:title>
   <news:publication_date>2026-05-10T22:16:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688755</loc>
  <lastmod>2026-05-10T22:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程に基づくベイズ的密度推定の効率化（Efficient Bayesian Inference for a Gaussian Process Density Model）</news:title>
   <news:publication_date>2026-05-10T22:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688753</loc>
  <lastmod>2026-05-10T22:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像と深層畳み込みニューラルネットワークによる米種分類（Rice Classification Using Spatio-Spectral Deep Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-10T22:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688751</loc>
  <lastmod>2026-05-10T22:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LTE RACHの衝突数推定を機械学習で可能にする手法（Enabling LTE RACH Collision Multiplicity Detection via Machine Learning）</news:title>
   <news:publication_date>2026-05-10T22:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688749</loc>
  <lastmod>2026-05-10T22:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像の変動性を生成モデルで補う（Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-10T22:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688747</loc>
  <lastmod>2026-05-10T21:23:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習における「高潔な安全性」の提示（Virtuous Safety in Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-10T21:23:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688745</loc>
  <lastmod>2026-05-10T21:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>型付き意味代数によるAMR依存構文解析（AMR Dependency Parsing with a Typed Semantic Algebra）</news:title>
   <news:publication_date>2026-05-10T21:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688743</loc>
  <lastmod>2026-05-10T21:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆アイジング問題に対する解析解（An Analytic Solution to the Inverse Ising Problem in the Tree-reweighted Approximation）</news:title>
   <news:publication_date>2026-05-10T21:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688741</loc>
  <lastmod>2026-05-10T21:23:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散特徴下における教師あり学習（SUPERVISED LEARNING UNDER DISTRIBUTED FEATURES）</news:title>
   <news:publication_date>2026-05-10T21:23:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688739</loc>
  <lastmod>2026-05-10T21:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続線形回帰における全域的後悔境界の確立（Uniform regret bounds over Rd for the sequential linear regression problem with the square loss）</news:title>
   <news:publication_date>2026-05-10T21:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688737</loc>
  <lastmod>2026-05-10T21:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みネットワークのチャネル削減と実運用性の革新（A novel channel pruning method for deep neural network compression）</news:title>
   <news:publication_date>2026-05-10T21:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688735</loc>
  <lastmod>2026-05-10T21:22:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUネットワークと多項式カーネルの表現力（Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis）</news:title>
   <news:publication_date>2026-05-10T21:22:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688733</loc>
  <lastmod>2026-05-10T20:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次ベイズ推論のためのカーネル写像埋め込み：変分マッピング粒子フィルタ (Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter)</news:title>
   <news:publication_date>2026-05-10T20:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688731</loc>
  <lastmod>2026-05-10T20:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルで制約を学習して人員ロスターを自動化する（Automating Personnel Rostering by Learning Constraints Using Tensors）</news:title>
   <news:publication_date>2026-05-10T20:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688729</loc>
  <lastmod>2026-05-10T20:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>閉じ込められたフェルミガスの相互作用クエンチで現れる持続的振動（Persistent oscillations of the order parameter and interaction quench phase diagram）</news:title>
   <news:publication_date>2026-05-10T20:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688727</loc>
  <lastmod>2026-05-10T20:30:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子に着想を得た複素語埋め込み（Quantum-inspired Complex Word Embedding）</news:title>
   <news:publication_date>2026-05-10T20:30:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688725</loc>
  <lastmod>2026-05-10T20:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全統計的ニューラル信念追跡（Fully Statistical Neural Belief Tracking）</news:title>
   <news:publication_date>2026-05-10T20:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688723</loc>
  <lastmod>2026-05-10T20:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lovász Convolutional Networks（Lovász Convolutional Networks）</news:title>
   <news:publication_date>2026-05-10T20:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688721</loc>
  <lastmod>2026-05-10T20:30:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CocoNetによる座標→色マッピングの新潮流（CocoNet: A Deep Neural Network for Mapping Pixel Coordinates to Color Values）</news:title>
   <news:publication_date>2026-05-10T20:30:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688719</loc>
  <lastmod>2026-05-10T19:39:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経ネットワークのアンカードアンサンブルによるベイズ推論と強化学習への応用（Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Exploration in Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-10T19:39:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688717</loc>
  <lastmod>2026-05-10T19:32:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性ゲート付きネットワークによる土地被覆セグメンテーション（Uncertainty Gated Network for Land Cover Segmentation）</news:title>
   <news:publication_date>2026-05-10T19:32:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688715</loc>
  <lastmod>2026-05-10T19:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオにおける点監視による行動局所化（Pointly-Supervised Action Localization）</news:title>
   <news:publication_date>2026-05-10T19:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688713</loc>
  <lastmod>2026-05-10T19:31:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハミルトニアン変分オートエンコーダー（Hamiltonian Variational Auto-Encoder）</news:title>
   <news:publication_date>2026-05-10T19:31:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688711</loc>
  <lastmod>2026-05-10T19:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価予測におけるニューラルネットワークの実用性と限界（Neural networks for stock price prediction）</news:title>
   <news:publication_date>2026-05-10T19:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688709</loc>
  <lastmod>2026-05-10T19:30:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Baidu検索ボリュームを用いたCSI300ボラティリティ予測のための長短期記憶ネットワーク（LONG SHORT-TERM MEMORY NETWORKS FOR CSI300 VOLATILITY PREDICTION WITH BAIDU SEARCH VOLUME）</news:title>
   <news:publication_date>2026-05-10T19:30:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688707</loc>
  <lastmod>2026-05-10T19:29:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量な確率的深層ネットワーク（Lightweight Probabilistic Deep Networks）</news:title>
   <news:publication_date>2026-05-10T19:29:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688705</loc>
  <lastmod>2026-05-10T18:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein変分推論の実践と要点（Wasserstein Variational Inference）</news:title>
   <news:publication_date>2026-05-10T18:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688703</loc>
  <lastmod>2026-05-10T18:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍セグメンテーションのための学習データ拡張（Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-10T18:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688701</loc>
  <lastmod>2026-05-10T18:38:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフのための深層埋め込み手法（DynGEM: Deep Embedding Method for Dynamic Graphs）</news:title>
   <news:publication_date>2026-05-10T18:38:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688699</loc>
  <lastmod>2026-05-10T18:38:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合分布の微分エントロピー：新しい上界と下界（The Differential Entropy of Mixtures: New Bounds and Applications）</news:title>
   <news:publication_date>2026-05-10T18:38:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688697</loc>
  <lastmod>2026-05-10T18:37:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース線形回帰の統計力学解析（Statistical mechanical analysis of sparse linear regression as a variable selection problem）</news:title>
   <news:publication_date>2026-05-10T18:37:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688695</loc>
  <lastmod>2026-05-10T18:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良された混合例データ拡張（Improved Mixed-Example Data Augmentation）</news:title>
   <news:publication_date>2026-05-10T18:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688693</loc>
  <lastmod>2026-05-10T18:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル感覚データの表現学習における分割による解きほぐし（Disentangling by Partitioning: A Representation Learning Framework for Multimodal Sensory Data）</news:title>
   <news:publication_date>2026-05-10T18:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688691</loc>
  <lastmod>2026-05-10T17:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ分類器の堅牢なトリミング手法（On Robust Trimming of Bayesian Network Classifiers）</news:title>
   <news:publication_date>2026-05-10T17:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688689</loc>
  <lastmod>2026-05-10T17:46:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子アナログ・デジタル変換の概観（Quantum analog-digital conversion）</news:title>
   <news:publication_date>2026-05-10T17:46:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688687</loc>
  <lastmod>2026-05-10T17:46:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計画打ち切り型方策探索（Truncated Horizon Policy Search）</news:title>
   <news:publication_date>2026-05-10T17:46:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688685</loc>
  <lastmod>2026-05-10T17:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通貨為替予測における機械学習と遺伝的アルゴリズム、テクニカル分析の統合（Currency exchange prediction using machine learning, genetic algorithms and technical analysis）</news:title>
   <news:publication_date>2026-05-10T17:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688683</loc>
  <lastmod>2026-05-10T17:45:43Z</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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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/688669</loc>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/688665</loc>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/688661</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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:genres>Blog</news:genres>
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