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   <news:title>星の元素組成で予測する系外惑星候補（A Recommendation Algorithm to Predict Giant Exoplanet Host Stars Using Stellar Elemental Abundances）</news:title>
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   <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>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>機械学習で探る多体局在：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>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <lastmod>2026-05-11T14:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <lastmod>2026-05-11T13:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>CuisineNetに基づく食の属性分類（CuisineNet: Food Attributes Classification using Multi-scale Convolution Network）</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>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>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-11T13:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <lastmod>2026-05-11T13:45:27Z</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>コードスイッチの固有表現認識における語彙外語への効率的対処のためのバイリンガル文字表現 (Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition)</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-11T13:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-11T13:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>頑健な場所カテゴリ分類とドメイン一般化（Robust Place Categorization with Deep Domain Generalization）</news:title>
   <news:publication_date>2026-05-11T13:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <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>
   <news:title>Sobolev Descent による分布移動の実用的理解（Sobolev Descent）</news:title>
   <news:publication_date>2026-05-11T13:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <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>
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   <news:title>郡単位のトウモロコシ収量予測における深層LSTMモデルの活用 (Predicting County Level Corn Yields Using Deep Long Short Term Memory Models)</news:title>
   <news:publication_date>2026-05-11T12:52:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-11T12:52:29Z</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>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>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/688982</loc>
  <lastmod>2026-05-11T12:51:39Z</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>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>
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  <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>
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   <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>
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  <loc>https://aibr.jp/archives/688978</loc>
  <lastmod>2026-05-11T12:50:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>未知ドメインへの一般化を促す敵対的データ増強（Generalizing to Unseen Domains via Adversarial Data Augmentation）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-11T12:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ランジュバン力学による敵対的攻撃への堅牢化（Robustifying Models Against Adversarial Attacks by Langevin Dynamics）</news:title>
   <news:publication_date>2026-05-11T12:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/688974</loc>
  <lastmod>2026-05-11T12:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <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>
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   <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>
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  <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>
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  <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>
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 <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>
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  <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>
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   <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>
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  <lastmod>2026-05-11T11:57:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <lastmod>2026-05-11T11:56:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <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>
   <news:title>ローライト画像解析のためのExclusively Darkデータセット（Getting to Know Low-light Images with The Exclusively Dark Dataset）</news:title>
   <news:publication_date>2026-05-10T17:45:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688681</loc>
  <lastmod>2026-05-10T17:45:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復再訓練による重み量子化の実用性と示唆（Retraining-Based Iterative Weight Quantization for Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-10T17:45:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688679</loc>
  <lastmod>2026-05-10T17:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索型構造予測のための知識蒸留（Knowledge Distillation for Search-based Structured Prediction）</news:title>
   <news:publication_date>2026-05-10T17:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688677</loc>
  <lastmod>2026-05-10T16:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ異常検知と局所化のためのガウス混合完全畳み込み変分オートエンコーダ（Video Anomaly Detection and Localization via Gaussian Mixture Fully Convolutional Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-10T16:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688675</loc>
  <lastmod>2026-05-10T16:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みの教師なしアラインメントとWasserstein Procrustes（Unsupervised Alignment of Embeddings with Wasserstein Procrustes）</news:title>
   <news:publication_date>2026-05-10T16:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688673</loc>
  <lastmod>2026-05-10T16:53:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミニバッチによるAUC最適化の新手法（MBA: Mini-Batch AUC Optimization）</news:title>
   <news:publication_date>2026-05-10T16:53:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688671</loc>
  <lastmod>2026-05-10T16:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価値伝播ネットワークの実用的意義（Value Propagation Networks）</news:title>
   <news:publication_date>2026-05-10T16:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688669</loc>
  <lastmod>2026-05-10T16:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性に配慮した生成モデル FairGAN（FairGAN: Fairness-aware Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-10T16:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688667</loc>
  <lastmod>2026-05-10T16:52:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CapsNetの画像分類における比較評価（CapsNet comparative performance evaluation for image classification）</news:title>
   <news:publication_date>2026-05-10T16:52:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688665</loc>
  <lastmod>2026-05-10T16:51:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称正定値行列上の統計的再帰モデル（A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices）</news:title>
   <news:publication_date>2026-05-10T16:51:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688663</loc>
  <lastmod>2026-05-10T16:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合関数による普遍的グラフ埋め込み（GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning）</news:title>
   <news:publication_date>2026-05-10T16:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688661</loc>
  <lastmod>2026-05-10T15:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散・完全非中央集権最適化におけるサイバーセキュリティ：歪み・ノイズ注入・ADMM（Cybersecurity in Distributed and Fully-Decentralized Optimization: Distortions, Noise Injection, and ADMM）</news:title>
   <news:publication_date>2026-05-10T15:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688659</loc>
  <lastmod>2026-05-10T15:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータで学ぶ：画像分類における多様化サブセット選択と能動学習（Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks）</news:title>
   <news:publication_date>2026-05-10T15:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688657</loc>
  <lastmod>2026-05-10T15:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙フィルタリングによるOOV除去（Graph-based Filtering of Out-of-Vocabulary Words for Encoder-Decoder Models）</news:title>
   <news:publication_date>2026-05-10T15:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688655</loc>
  <lastmod>2026-05-10T15:50:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算的蛍光顕微鏡法の提案（Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles）</news:title>
   <news:publication_date>2026-05-10T15:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688653</loc>
  <lastmod>2026-05-10T15:50:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多成分ボース＝アインシュタイン凝縮体における超流動ドラッグ（Superfluid Drag in Multicomponent Bose-Einstein Condensates on a Square Optical Lattice）</news:title>
   <news:publication_date>2026-05-10T15:50:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688651</loc>
  <lastmod>2026-05-10T15:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半暗黙変分推論（Semi-Implicit Variational Inference）</news:title>
   <news:publication_date>2026-05-10T15:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688649</loc>
  <lastmod>2026-05-10T14:59:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バルジ方向の球状星団に対するHST深宇宙撮像（DEEP HST IMAGING OF GLOBULAR CLUSTERS TOWARDS THE GALACTIC BULGE: OBSERVATIONS, DATA REDUCTION, AND COLOR-MAGNITUDE DIAGRAMS）</news:title>
   <news:publication_date>2026-05-10T14:59:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688647</loc>
  <lastmod>2026-05-10T14:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Exemplar Guided &amp;amp; Semantically Consistent Image-to-image Translation（EXEMPLAR GUIDED UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION WITH SEMANTIC CONSISTENCY）</news:title>
   <news:publication_date>2026-05-10T14:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688645</loc>
  <lastmod>2026-05-10T14:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アーティスティックな「様式」を無教師で学ぶ：Archetypal Style Analysis（Unsupervised Learning of Artistic Styles with Archetypal Style Analysis）</news:title>
   <news:publication_date>2026-05-10T14:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688643</loc>
  <lastmod>2026-05-10T14:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NengoDLによる深層学習と神経模倣の融合（NengoDL: Combining deep learning and neuromorphic modelling methods）</news:title>
   <news:publication_date>2026-05-10T14:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688641</loc>
  <lastmod>2026-05-10T14:57:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像推定の統計的学習法（Statistical Learning in Computed Tomography Image Estimation）</news:title>
   <news:publication_date>2026-05-10T14:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688639</loc>
  <lastmod>2026-05-10T14:57:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能パーティクルフィルタ：アルゴリズムプリオリを用いたエンドツーエンド学習（Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors）</news:title>
   <news:publication_date>2026-05-10T14:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688637</loc>
  <lastmod>2026-05-10T14:57:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Global Sum Poolingによる大画像少データ環境下での物体カウント改善（Global Sum Pooling: A Generalization Trick for Object Counting with Small Datasets of Large Images）</news:title>
   <news:publication_date>2026-05-10T14:57:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688635</loc>
  <lastmod>2026-05-10T14:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドーパミンによる生体準拠ニューロモジュレーション回路—eSTDP/iSTDPの電子回路設計とシミュレーション (Electronic schematic for bio-plausible dopamine neuromodulation of eSTDP and iSTDP)</news:title>
   <news:publication_date>2026-05-10T14:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688633</loc>
  <lastmod>2026-05-10T14:05:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と触覚で学ぶロボット把持と掴み直しの実践（More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch）</news:title>
   <news:publication_date>2026-05-10T14:05:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688631</loc>
  <lastmod>2026-05-10T14:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一ネットワークへの新規タスク追加方法：バイナリマスクを用いた重み変換（Adding New Tasks to a Single Network with Weight Transformations using Binary Masks）</news:title>
   <news:publication_date>2026-05-10T14:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688629</loc>
  <lastmod>2026-05-10T14:04:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非二分岐系統樹推定のための適応的LASSO（Non-bifurcating Phylogenetic Tree Inference via the Adaptive Lasso）</news:title>
   <news:publication_date>2026-05-10T14:04:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688627</loc>
  <lastmod>2026-05-10T14:04:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬制約付き方策最適化（Reward Constrained Policy Optimization）</news:title>
   <news:publication_date>2026-05-10T14:04:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688625</loc>
  <lastmod>2026-05-10T14:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型無線ネットワークにおける多腕バンディットの可能性と限界（Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs）</news:title>
   <news:publication_date>2026-05-10T14:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688623</loc>
  <lastmod>2026-05-10T14:03:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書の高速抽象要約と強化学習による文選択の刷新（Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting）</news:title>
   <news:publication_date>2026-05-10T14:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688621</loc>
  <lastmod>2026-05-10T13:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック単位で学ぶ画質改善と圧縮の統合手法（BlockCNN: A Deep Network for Artifact Removal and Image Compression）</news:title>
   <news:publication_date>2026-05-10T13:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688619</loc>
  <lastmod>2026-05-10T13:12:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布保存型生成モデルによる損失性圧縮（Deep Generative Models for Distribution-Preserving Lossy Compression）</news:title>
   <news:publication_date>2026-05-10T13:12:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688617</loc>
  <lastmod>2026-05-10T13:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散潜在表現を扱うVQ-VAEの理論と実践（Theory and Experiments on Vector Quantized Autoencoders）</news:title>
   <news:publication_date>2026-05-10T13:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688615</loc>
  <lastmod>2026-05-10T13:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意のデータを自己符号化するカーネル自己符号化器（Autoencoding any Data through Kernel Autoencoders）</news:title>
   <news:publication_date>2026-05-10T13:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688613</loc>
  <lastmod>2026-05-10T13:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル観測によるオンライン影響力最大化（Online Influence Maximization with Local Observations）</news:title>
   <news:publication_date>2026-05-10T13:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688611</loc>
  <lastmod>2026-05-10T13:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルの柔軟かつ高精度な推論と学習（Flexible and accurate inference and learning for deep generative models）</news:title>
   <news:publication_date>2026-05-10T13:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688609</loc>
  <lastmod>2026-05-10T13:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワークにおけるポアソン・ガンマ潜在所属モデル（A Poisson Gamma Probabilistic Model for Latent Node-group Memberships in Dynamic Networks）</news:title>
   <news:publication_date>2026-05-10T13:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688607</loc>
  <lastmod>2026-05-10T12:20:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数学の壁を越える：物理学初学者のための必須数学ガイド (Tunneling Through the Math Barrier)</news:title>
   <news:publication_date>2026-05-10T12:20:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688605</loc>
  <lastmod>2026-05-10T12:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を持つ自己対話学習の提案（Memory Augmented Self-Play）</news:title>
   <news:publication_date>2026-05-10T12:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688603</loc>
  <lastmod>2026-05-10T12:20:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズか否か、もはや問いではない（To Bayes or Not To Bayes?）</news:title>
   <news:publication_date>2026-05-10T12:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688601</loc>
  <lastmod>2026-05-10T12:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された脆弱性検出・悪用・修補の総覧（The Coming Era of AlphaHacking? A Survey of Automatic Software Vulnerability Detection, Exploitation and Patching Techniques）</news:title>
   <news:publication_date>2026-05-10T12:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688599</loc>
  <lastmod>2026-05-10T12:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序埋め込みを用いた異種属性を持つアイテム推薦（A Sequential Embedding Approach for Item Recommendation with Heterogeneous Attributes）</news:title>
   <news:publication_date>2026-05-10T12:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688597</loc>
  <lastmod>2026-05-10T12:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による車載クラウドの資源配分（Reinforcement Learning for Resource Provisioning in Vehicular Cloud）</news:title>
   <news:publication_date>2026-05-10T12:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688595</loc>
  <lastmod>2026-05-10T12:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフト層固有のマルチタスク要約（Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation）</news:title>
   <news:publication_date>2026-05-10T12:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688593</loc>
  <lastmod>2026-05-10T11:28:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシングにおける敵対的サンプル（Adversarial Examples in Remote Sensing）</news:title>
   <news:publication_date>2026-05-10T11:28:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688591</loc>
  <lastmod>2026-05-10T11:28:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構とゲートを備えたグラフ畳み込みネットワークによる分子構造–物性関係の深層学習（Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network）</news:title>
   <news:publication_date>2026-05-10T11:28:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688589</loc>
  <lastmod>2026-05-10T11:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントコリファレンス解決のための表現学習とクラスタ指向正則化（Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization）</news:title>
   <news:publication_date>2026-05-10T11:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688587</loc>
  <lastmod>2026-05-10T11:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気脳磁図（MEG）データを解読する適応型ニューラルネットワーク分類器（Adaptive neural network classifier for decoding MEG signals）</news:title>
   <news:publication_date>2026-05-10T11:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688585</loc>
  <lastmod>2026-05-10T11:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ画像を用いた物語生成を改善するGLAC Net（GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story Generation）</news:title>
   <news:publication_date>2026-05-10T11:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688583</loc>
  <lastmod>2026-05-10T11:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習による時空間表現の獲得（Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization）</news:title>
   <news:publication_date>2026-05-10T11:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688581</loc>
  <lastmod>2026-05-10T11:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算資源を抑えるための精度の動的犠牲—ソフトマックス信頼度に基づくカスケード推論（Dynamically Sacrificing Accuracy for Reduced Computation: Cascaded Inference Based on Softmax Confidence）</news:title>
   <news:publication_date>2026-05-10T11:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688579</loc>
  <lastmod>2026-05-10T10:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのLipschitz正則性と効率的推定（Lipschitz regularity of deep neural networks: analysis and efficient estimation）</news:title>
   <news:publication_date>2026-05-10T10:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688577</loc>
  <lastmod>2026-05-10T10:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子–陽子超周辺衝突におけるベクトル中間子の光生成（Photoproduction of vector mesons in proton-proton ultraperipheral collisions at the Larger Hadron Collider）</news:title>
   <news:publication_date>2026-05-10T10:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688575</loc>
  <lastmod>2026-05-10T10:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散フロー事後分布による変分推論の高速化（Discrete flow posteriors for variational inference in discrete dynamical systems）</news:title>
   <news:publication_date>2026-05-10T10:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688573</loc>
  <lastmod>2026-05-10T10:35:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙のリッジ正則化と最適リッジ罰則の再考（Implicit Ridge Regularization）</news:title>
   <news:publication_date>2026-05-10T10:35:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688571</loc>
  <lastmod>2026-05-10T10:35:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的超解像と識別情報を使った顔ハルシネーション（Face hallucination using cascaded super-resolution and identity priors）</news:title>
   <news:publication_date>2026-05-10T10:35:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688569</loc>
  <lastmod>2026-05-10T10:34:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何変換を用いた深層異常検知（Deep Anomaly Detection Using Geometric Transformations）</news:title>
   <news:publication_date>2026-05-10T10:34:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688567</loc>
  <lastmod>2026-05-10T10:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模で較正された分類のためのディリクレ基底ガウス過程（Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification）</news:title>
   <news:publication_date>2026-05-10T10:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688565</loc>
  <lastmod>2026-05-10T09:43:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的クラスタリングを強化する深層Q学習の応用（Hierarchical clustering with deep Q-learning）</news:title>
   <news:publication_date>2026-05-10T09:43:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688563</loc>
  <lastmod>2026-05-10T09:41:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力依存の変分ベータ・ベルヌーイドロップアウトによるネットワーク圧縮（Adaptive Network Sparsiﬁcation with Dependent Variational Beta-Bernoulli Dropout）</news:title>
   <news:publication_date>2026-05-10T09:41:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688561</loc>
  <lastmod>2026-05-10T09:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M87のX線点源を深掘りするChandra観測（DEEP CHANDRA OBSERVATIONS OF X-RAY POINT SOURCES IN M87）</news:title>
   <news:publication_date>2026-05-10T09:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688559</loc>
  <lastmod>2026-05-10T09:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルのみから極値統計を予測する機械学習の応用（Machine learning for prediction of extreme statistics in modulation instability）</news:title>
   <news:publication_date>2026-05-10T09:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688557</loc>
  <lastmod>2026-05-10T09:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプルの重要度重み付き転移学習（Importance Weighted Transfer of Samples in Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-10T09:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688555</loc>
  <lastmod>2026-05-10T09:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線科医の訓練方式を模した医用画像解析システムの学習（Training Medical Image Analysis Systems like Radiologists）</news:title>
   <news:publication_date>2026-05-10T09:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688553</loc>
  <lastmod>2026-05-10T09:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変ビットレートに最適化したブロック単位ニューラル画像圧縮（Block-optimized Variable Bit Rate Neural Image Compression）</news:title>
   <news:publication_date>2026-05-10T09:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688551</loc>
  <lastmod>2026-05-10T08:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微小なラベルずれが畳み込みニューラルネットに与える影響（INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING）</news:title>
   <news:publication_date>2026-05-10T08:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688549</loc>
  <lastmod>2026-05-10T08:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepProbLogによるニューラル確率論理プログラミング（DeepProbLog: Neural Probabilistic Logic Programming）</news:title>
   <news:publication_date>2026-05-10T08:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688547</loc>
  <lastmod>2026-05-10T08:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続値を条件に生成するVAR+GANの概観（Versatile Auxiliary Regressor with Generative Adversarial network）</news:title>
   <news:publication_date>2026-05-10T08:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688545</loc>
  <lastmod>2026-05-10T08:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>第四次勾配展開に基づく運動エネルギー密度の評価と機械学習による改善（Kinetic energy densities based on the fourth order gradient expansion）</news:title>
   <news:publication_date>2026-05-10T08:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688543</loc>
  <lastmod>2026-05-10T08:47:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的デコーダを用いたニューラル機械翻訳（A Stochastic Decoder for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-10T08:47:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688541</loc>
  <lastmod>2026-05-10T08:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散重み統合による脳画像セグメンテーション（Distributed Weight Consolidation: A Brain Segmentation Case Study）</news:title>
   <news:publication_date>2026-05-10T08:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688539</loc>
  <lastmod>2026-05-10T08:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>r-instanceによる迷子情報検出の統合的アプローチ（r-instance Learning for Missing People Tweets Identification）</news:title>
   <news:publication_date>2026-05-10T08:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688537</loc>
  <lastmod>2026-05-10T07:56:02Z</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・クロネッカー因子によるリアルタイム再帰学習の近似（Approximating Real-Time Recurrent Learning with Random Kronecker Factors）</news:title>
   <news:publication_date>2026-05-10T07:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688535</loc>
  <lastmod>2026-05-10T07:55:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ学習におけるワッサースタイン重心の活用（Bayesian Learning with Wasserstein Barycenters）</news:title>
   <news:publication_date>2026-05-10T07:55:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688533</loc>
  <lastmod>2026-05-10T07:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sigsoftmaxによるソフトマックスの表現力突破（Sigsoftmax: Reanalysis of the Softmax Bottleneck）</news:title>
   <news:publication_date>2026-05-10T07:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688531</loc>
  <lastmod>2026-05-10T07:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペイン語ツイートの感情強度推定におけるデータ拡張と半教師あり学習の効果（UG18 at SemEval-2018 Task 1: Generating Additional Training Data for Predicting Emotion Intensity in Spanish）</news:title>
   <news:publication_date>2026-05-10T07:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688529</loc>
  <lastmod>2026-05-10T07:54:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス判定の局所的ルール説明（Local Rule-Based Explanations of Black Box Decision Systems）</news:title>
   <news:publication_date>2026-05-10T07:54:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688527</loc>
  <lastmod>2026-05-10T07:53:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムパターンの時間的構造の学習（Learning Temporal Structures of Random Patterns）</news:title>
   <news:publication_date>2026-05-10T07:53:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688525</loc>
  <lastmod>2026-05-10T07:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPGPUを用いた線形時間t-SNE最適化（GPGPU Linear Complexity t-SNE Optimization）</news:title>
   <news:publication_date>2026-05-10T07:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/688523</loc>
  <lastmod>2026-05-10T07:02:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenNMT: ニューラル機械翻訳ツールキット（OpenNMT: Neural Machine Translation Toolkit）</news:title>
   <news:publication_date>2026-05-10T07:02:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688521</loc>
  <lastmod>2026-05-10T07:01:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きカーネル密度推定に基づく高速動的ルーティング（Fast Dynamic Routing Based on Weighted Kernel Density Estimation）</news:title>
   <news:publication_date>2026-05-10T07:01:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688519</loc>
  <lastmod>2026-05-10T07:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実数値パラメータで制御するRNNによる対話的音響合成（Real-valued parametric conditioning of an RNN for interactive sound synthesis）</news:title>
   <news:publication_date>2026-05-10T07:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688517</loc>
  <lastmod>2026-05-10T07:01:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングのための深い識別潜在空間（Deep Discriminative Latent Space for Clustering）</news:title>
   <news:publication_date>2026-05-10T07:01:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688515</loc>
  <lastmod>2026-05-10T07:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理向け畳み込みニューラルネットワークの圧縮技術（Convolutional neural network compression for natural language processing）</news:title>
   <news:publication_date>2026-05-10T07:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688513</loc>
  <lastmod>2026-05-10T07:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CTからMRを合成する深層学習：ペアデータと非ペアデータを併用するアプローチ（Deep CT to MR Synthesis using Paired and Unpaired Data）</news:title>
   <news:publication_date>2026-05-10T07:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688511</loc>
  <lastmod>2026-05-10T07:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パブロフ条件付けにおける行動安定性と個体差の拡張モデル（Behavior stability and individual differences in Pavlovian extended conditioning）</news:title>
   <news:publication_date>2026-05-10T07:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688509</loc>
  <lastmod>2026-05-10T06:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小天体周回の安定周期軌道の設計（Stable Periodic Orbits for Spacecrafts around Minor Celestial Bodies）</news:title>
   <news:publication_date>2026-05-10T06:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688507</loc>
  <lastmod>2026-05-10T06:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Trustworthy Knowledge Tracing（Deep Trustworthy Knowledge Tracing）</news:title>
   <news:publication_date>2026-05-10T06:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688505</loc>
  <lastmod>2026-05-10T06:01:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活動的小惑星358Pの核の観測と回転性の検証（Nucleus of active asteroid 358P/Pan-STARRS (P/2012 T1)）</news:title>
   <news:publication_date>2026-05-10T06:01:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688503</loc>
  <lastmod>2026-05-10T06:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GenAttack：勾配情報を使わない実践的ブラックボックス攻撃（GenAttack: Practical Black-box Attacks with Gradient-Free Optimization）</news:title>
   <news:publication_date>2026-05-10T06:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688501</loc>
  <lastmod>2026-05-10T05:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次特徴空間を制約して知識を保持する継続学習（Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks）</news:title>
   <news:publication_date>2026-05-10T05:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688499</loc>
  <lastmod>2026-05-10T05:59:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークの普遍性（Universality of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-10T05:59:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688497</loc>
  <lastmod>2026-05-10T05:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オブジェクトレベル表現による少ショット画像分類（Object-Level Representation Learning for Few-Shot Image Classification）</news:title>
   <news:publication_date>2026-05-10T05:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688495</loc>
  <lastmod>2026-05-10T05:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークの一般化と最適化性能の理解（Understanding Generalization and Optimization Performance of Deep CNNs）</news:title>
   <news:publication_date>2026-05-10T05:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688493</loc>
  <lastmod>2026-05-10T05:07:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN特徴マップの解像度を効率的に改善するマルチサンプリング（Improving the Resolution of CNN Feature Maps Efficiently with Multisampling）</news:title>
   <news:publication_date>2026-05-10T05:07:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688491</loc>
  <lastmod>2026-05-10T05:07:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス認識型物体検出と決定点過程による重なり物体の改善（Learning Instance-Aware Object Detection Using Determinantal Point Processes）</news:title>
   <news:publication_date>2026-05-10T05:07:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688489</loc>
  <lastmod>2026-05-10T05:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波画像における深層敵対的文脈認識ランドマーク検出（Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging）</news:title>
   <news:publication_date>2026-05-10T05:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688487</loc>
  <lastmod>2026-05-10T05:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dual Policy Iteration（Dual Policy Iteration）</news:title>
   <news:publication_date>2026-05-10T05:06:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688485</loc>
  <lastmod>2026-05-10T05:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的な次元で群を分ける手法の要点（Clustering by latent dimensions）</news:title>
   <news:publication_date>2026-05-10T05:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688483</loc>
  <lastmod>2026-05-10T05:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未来フレーム予測で学習したニューラルネットワークは生物学的ニューロン応答と知覚の重要特性を模倣する（A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception）</news:title>
   <news:publication_date>2026-05-10T05:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688481</loc>
  <lastmod>2026-05-10T04:15:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EMRを解きほぐす可視解析と解釈可能なRNNの設計（RetainVis / RetainEX）</news:title>
   <news:publication_date>2026-05-10T04:15:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688479</loc>
  <lastmod>2026-05-10T04:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザーを深く知る：複数Eコマースタスクからの普遍的ユーザー表現（Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks）</news:title>
   <news:publication_date>2026-05-10T04:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688477</loc>
  <lastmod>2026-05-10T04:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LHCにおけるRパリティ破れ超対称性探索の深層学習（Deep learning for the R-parity violating supersymmetry searches at the LHC）</news:title>
   <news:publication_date>2026-05-10T04:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688475</loc>
  <lastmod>2026-05-10T04:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模天文データにおける複雑天体の自動検出法（Identifying Complex Sources in Large Astronomical Data Using a Coarse-Grained Complexity Measure）</news:title>
   <news:publication_date>2026-05-10T04:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688473</loc>
  <lastmod>2026-05-10T04:14:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーシステンス図から平面グラフを再構築する手法（Learning Simplicial Complexes from Persistence Diagrams）</news:title>
   <news:publication_date>2026-05-10T04:14:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688471</loc>
  <lastmod>2026-05-10T04:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別器特徴を再利用した潜在推定（Discriminator Feature-based Inference by Recycling the Discriminator of GANs）</news:title>
   <news:publication_date>2026-05-10T04:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688469</loc>
  <lastmod>2026-05-10T04:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ニューラルネットワークの微分学習則への架け橋（From statistical inference to a differential learning rule for stochastic neural networks）</news:title>
   <news:publication_date>2026-05-10T04:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688467</loc>
  <lastmod>2026-05-10T03:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における戦略耐性線形回帰（Strategyproof Linear Regression in High Dimensions）</news:title>
   <news:publication_date>2026-05-10T03:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688465</loc>
  <lastmod>2026-05-10T03:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークのコンパクトで計算効率の高い表現（Compact and Computationally Efficient Representation of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-10T03:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688463</loc>
  <lastmod>2026-05-10T03:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Batch Normalizationの指数的収束率（Exponential convergence rates for Batch Normalization）</news:title>
   <news:publication_date>2026-05-10T03:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688461</loc>
  <lastmod>2026-05-10T03:20:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パルスと撮像を協調させるSPIN（A Synergized Pulsing‑Imaging Network）</news:title>
   <news:publication_date>2026-05-10T03:20:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688459</loc>
  <lastmod>2026-05-10T03:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変形の敵対的正則化による画像レジストレーション学習（Adversarial Deformation Regularization for Training Image Registration Neural Networks）</news:title>
   <news:publication_date>2026-05-10T03:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688457</loc>
  <lastmod>2026-05-10T03:20:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法的文書検索における文書ベクトル埋め込みと深層学習（Legal Document Retrieval using Document Vector Embeddings and Deep Learning）</news:title>
   <news:publication_date>2026-05-10T03:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688455</loc>
  <lastmod>2026-05-10T03:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>余補完だが非補完なアーベル圏の構成（A COCOMPLETE BUT NOT COMPLETE ABELIAN CATEGORY）</news:title>
   <news:publication_date>2026-05-10T03:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688453</loc>
  <lastmod>2026-05-10T02:29:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN全体を利用した敵対的サンプル防御（Defending Against Adversarial Samples Using An Entire GAN）</news:title>
   <news:publication_date>2026-05-10T02:29:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688451</loc>
  <lastmod>2026-05-10T02:29:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト強化学習のためのフィンガープリント方策最適化（Fingerprint Policy Optimisation for Robust Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-10T02:29:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688449</loc>
  <lastmod>2026-05-10T02:28:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-10T02:28:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688447</loc>
  <lastmod>2026-05-10T02:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fog-RANにおける異種遅延要件を持つIoT向け強化学習ベースの資源割当（Reinforcement Learning-based Resource Allocation in Fog RAN for IoT with Heterogeneous Latency Requirements）</news:title>
   <news:publication_date>2026-05-10T02:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688445</loc>
  <lastmod>2026-05-10T02:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Contextual Graph Markov Modelの解説（Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing）</news:title>
   <news:publication_date>2026-05-10T02:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688443</loc>
  <lastmod>2026-05-10T02:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTによる省エネ建物管理の統合プラットフォーム（IoT for Green Building Management）</news:title>
   <news:publication_date>2026-05-10T02:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688441</loc>
  <lastmod>2026-05-10T02:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anderson加速を用いた高速K平均クラスタリング (Fast K-Means Clustering with Anderson Acceleration)</news:title>
   <news:publication_date>2026-05-10T02:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688439</loc>
  <lastmod>2026-05-10T01:37:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混雑場面における異常検知と局所化（Anomaly Detection and Localization in Crowded Scenes by Motion-field Shape Description and Similarity-based Statistical Learning）</news:title>
   <news:publication_date>2026-05-10T01:37:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688437</loc>
  <lastmod>2026-05-10T01:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のバンディットフィードバックで学ぶ翻訳強化（Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-10T01:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688435</loc>
  <lastmod>2026-05-10T01:36:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルセンサーによる人身取引の把握と監視（Understanding and Monitoring Human Trafficking via Social Sensors: A Sociological Approach）</news:title>
   <news:publication_date>2026-05-10T01:36:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688433</loc>
  <lastmod>2026-05-10T01:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所情報基準による動的システムのモデル選択（A Local Information Criterion for Dynamical Systems）</news:title>
   <news:publication_date>2026-05-10T01:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688431</loc>
  <lastmod>2026-05-10T01:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視カメラ向けカスタム深層学習映像解析の実装と評価（Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras）</news:title>
   <news:publication_date>2026-05-10T01:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688429</loc>
  <lastmod>2026-05-10T01:36:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワッサースタイン不確実性集合を用いたロバスト仮説検定（Robust Hypothesis Testing Using Wasserstein Uncertainty Sets）</news:title>
   <news:publication_date>2026-05-10T01:36:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688427</loc>
  <lastmod>2026-05-10T01:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測からの動的ネットワークモデル（Dynamic Network Model from Partial Observations）</news:title>
   <news:publication_date>2026-05-10T01:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688425</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>階層的に解釈可能な潜在表現を学ぶDTLC-GAN（Generative Adversarial Image Synthesis with Decision Tree Latent Controller）</news:title>
   <news:publication_date>2026-05-10T00:44:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688423</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>予測のための意味的説明（Semantic Explanations of Predictions）</news:title>
   <news:publication_date>2026-05-10T00:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688421</loc>
  <lastmod>2026-05-10T00:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学物質―疾病関係抽出における文字基盤単語埋め込みの有効性（Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings）</news:title>
   <news:publication_date>2026-05-10T00:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688419</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>ベイズ的量子回路の要点解説（Bayesian Quantum Circuit）</news:title>
   <news:publication_date>2026-05-10T00:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688417</loc>
  <lastmod>2026-05-10T00:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑らかで強凸な関数に対する頑健な加速勾配法（Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions）</news:title>
   <news:publication_date>2026-05-10T00:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688415</loc>
  <lastmod>2026-05-10T00:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検証指標を直接最適化する重み付き学習（Metric-Optimized Example Weights）</news:title>
   <news:publication_date>2026-05-10T00:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688413</loc>
  <lastmod>2026-05-10T00:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的注釈で特徴を分離する技術（Dual Swap Disentangling）</news:title>
   <news:publication_date>2026-05-10T00:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688411</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>時系列データの欠損値を双方向で学習して埋める手法（BRITS: Bidirectional Recurrent Imputation for Time Series）</news:title>
   <news:publication_date>2026-05-09T23:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688409</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>制約を学習する対話的枠組みが示す、ラベル負担の軽減（Adversarial Constraint Learning for Structured Prediction）</news:title>
   <news:publication_date>2026-05-09T23:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688407</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>通信効率と差分プライバシーを両立する分散SGD（cpSGD: Communication-efficient and differentially-private distributed SGD）</news:title>
   <news:publication_date>2026-05-09T23:49:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688405</loc>
  <lastmod>2026-05-09T23:49:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さなラベルから学ぶ深層学習の拡張手法（Transductive Label Augmentation for Improved Deep Network Learning）</news:title>
   <news:publication_date>2026-05-09T23:49:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688403</loc>
  <lastmod>2026-05-09T23:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DPW-SDNetによるJPEG圧縮画像のソフトデコーディング (Dual Pixel-Wavelet Domain Deep CNNs for Soft Decoding of JPEG-Compressed Images)</news:title>
   <news:publication_date>2026-05-09T23:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688401</loc>
  <lastmod>2026-05-09T23:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽譜上の小さな記号を捉える深層ウォーターシェッド検出器（Deep Watershed Detector for Music Object Recognition）</news:title>
   <news:publication_date>2026-05-09T23:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688399</loc>
  <lastmod>2026-05-09T23:47:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的表現学習による親族認証（Hierarchical Representation Learning for Kinship Verification）</news:title>
   <news:publication_date>2026-05-09T23:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688397</loc>
  <lastmod>2026-05-09T22:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文と問いの依存性を読む技術が示す実務価値（Dependent Gated Reading for Cloze-Style Question Answering）</news:title>
   <news:publication_date>2026-05-09T22:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688395</loc>
  <lastmod>2026-05-09T22:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習とSUREによる画像復元の再考（Unsupervised Learning with Stein’s Unbiased Risk Estimator）</news:title>
   <news:publication_date>2026-05-09T22:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688393</loc>
  <lastmod>2026-05-09T22:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主観的空間・時間パターンの代数表現（Algebraic Expression of Subjective Spatial and Temporal Patterns）</news:title>
   <news:publication_date>2026-05-09T22:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688391</loc>
  <lastmod>2026-05-09T22:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列逐次パターンマイニングの総覧（A Survey of Parallel Sequential Pattern Mining）</news:title>
   <news:publication_date>2026-05-09T22:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688389</loc>
  <lastmod>2026-05-09T22:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アイスホッケーにおける文脈対応型選手評価を実現する深層強化学習（Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation）</news:title>
   <news:publication_date>2026-05-09T22:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688387</loc>
  <lastmod>2026-05-09T22:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みガウス過程の較正（Calibrating Deep Convolutional Gaussian Processes）</news:title>
   <news:publication_date>2026-05-09T22:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688385</loc>
  <lastmod>2026-05-09T22:52:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想教室の未来：既存機能で対面の限界を超える（The Future of Virtual Classroom: Using Existing Features to Move Beyond Traditional Classroom Limitations）</news:title>
   <news:publication_date>2026-05-09T22:52:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688383</loc>
  <lastmod>2026-05-09T22:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンド絶縁体のトポロジカル不変量を深層学習で学習する（Deep Learning Topological Invariants of Band Insulators）</news:title>
   <news:publication_date>2026-05-09T22:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688381</loc>
  <lastmod>2026-05-09T21:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔音声認識における自動コンテキスト窓構成（Automatic context window composition for distant speech recognition）</news:title>
   <news:publication_date>2026-05-09T21:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688379</loc>
  <lastmod>2026-05-09T21:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレアの典型的Mg IIスペクトルを機械学習で同定する（IDENTIFYING TYPICAL MG II FLARE SPECTRA USING MACHINE LEARNING）</news:title>
   <news:publication_date>2026-05-09T21:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/688377</loc>
  <lastmod>2026-05-09T21:58:13Z</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での安定な測地線更新とPoincaré埋め込みへの応用 (Stable Geodesic Update on Hyperbolic Space and its Application to Poincaré Embeddings)</news:title>
   <news:publication_date>2026-05-09T21:58:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688375</loc>
  <lastmod>2026-05-09T21:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAMA/LIBRA–phase2の独立検証的結果（First model independent results from DAMA/LIBRA–phase2）</news:title>
   <news:publication_date>2026-05-09T21:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688373</loc>
  <lastmod>2026-05-09T21:57:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スプレッドシートの「匂い」を組み合わせて不具合を予測する方法（Combining Spreadsheet Smells for Improved Fault Prediction）</news:title>
   <news:publication_date>2026-05-09T21:57:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688371</loc>
  <lastmod>2026-05-09T21:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所目標伝播に基づく生物学的動機付けアルゴリズム（Biologically Motivated Algorithms for Propagating Local Target Representations）</news:title>
   <news:publication_date>2026-05-09T21:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688369</loc>
  <lastmod>2026-05-09T21:05:43Z</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・映像からの車両インスタンス分割（Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network）</news:title>
   <news:publication_date>2026-05-09T21:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688367</loc>
  <lastmod>2026-05-09T21:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Apache SAMOA によるストリーム学習の大規模化（Large-Scale Learning from Data Streams with Apache SAMOA）</news:title>
   <news:publication_date>2026-05-09T21:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688365</loc>
  <lastmod>2026-05-09T21:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンレイヤーニューラルネットワークに基づく非線形帰納行列補完（Nonlinear Inductive Matrix Completion based on One-layer Neural Networks）</news:title>
   <news:publication_date>2026-05-09T21:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688363</loc>
  <lastmod>2026-05-09T21:03:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上でのCNN推論高速化サーベイ（Accelerating CNN inference on FPGAs: A Survey）</news:title>
   <news:publication_date>2026-05-09T21:03:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688361</loc>
  <lastmod>2026-05-09T21:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リウェイテッド・ウェイクスリープによる確率的制御フローモデル学習の再検討 (Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow)</news:title>
   <news:publication_date>2026-05-09T21:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688359</loc>
  <lastmod>2026-05-09T21:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法の正則化的性質（On the Regularizing Property of Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-05-09T21:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688357</loc>
  <lastmod>2026-05-09T21:02:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識に強いL1-2D2PCANet（L1-2D2PCANet: A Deep Learning Network for Face Recognition）</news:title>
   <news:publication_date>2026-05-09T21:02:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688355</loc>
  <lastmod>2026-05-09T20:10:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフ埋め込みからオントロジー埋め込みへ（From Knowledge Graph Embedding to Ontology Embedding?）</news:title>
   <news:publication_date>2026-05-09T20:10:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688353</loc>
  <lastmod>2026-05-09T20:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の幾何学的理解（Geometric Understanding of Deep Learning）</news:title>
   <news:publication_date>2026-05-09T20:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688351</loc>
  <lastmod>2026-05-09T20:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KDD Cup 99 の徹底前処理と機械学習による侵入検知性能評価（Intensive Preprocessing of KDD Cup 99 for Network Intrusion Classification Using Machine Learning Techniques）</news:title>
   <news:publication_date>2026-05-09T20:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688349</loc>
  <lastmod>2026-05-09T20:08:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>象とロバとコロネル・ブロット：政治的言説をデータで見る新しい枠組み（Elephants, Donkeys, and Colonel Blotto）</news:title>
   <news:publication_date>2026-05-09T20:08:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688347</loc>
  <lastmod>2026-05-09T20:08:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面上の多チャンネル疎ブラインドデコンボリューション（Multichannel Sparse Blind Deconvolution on the Sphere）</news:title>
   <news:publication_date>2026-05-09T20:08:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688345</loc>
  <lastmod>2026-05-09T20:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明るいF型星を周回する膨張ホット・ジュピターの発見（NGTS-2b: An inflated hot-Jupiter transiting a bright F-dwarf）</news:title>
   <news:publication_date>2026-05-09T20:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688343</loc>
  <lastmod>2026-05-09T20:07:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像からの精密年齢推定とAttention LSTM（Fine-Grained Age Estimation in the Wild with Attention LSTM Networks）</news:title>
   <news:publication_date>2026-05-09T20:07:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688341</loc>
  <lastmod>2026-05-09T19:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコード識別子の分割における双方向LSTMの応用（Splitting source code identifiers using Bidirectional LSTM Recurrent Neural Network）</news:title>
   <news:publication_date>2026-05-09T19:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688339</loc>
  <lastmod>2026-05-09T19:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ市場におけるモデルベース価格設定（Model-based Pricing for Machine Learning in a Data Marketplace）</news:title>
   <news:publication_date>2026-05-09T19:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688337</loc>
  <lastmod>2026-05-09T19:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣と強化の組合せで速やかに学習する方法（Fast Policy Learning through Imitation and Reinforcement）</news:title>
   <news:publication_date>2026-05-09T19:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688335</loc>
  <lastmod>2026-05-09T19:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Huberのϵ汚染モデル下におけるロバスト非パラメトリック回帰（Robust Nonparametric Regression under Huber’s ϵ-contamination Model）</news:title>
   <news:publication_date>2026-05-09T19:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688333</loc>
  <lastmod>2026-05-09T19:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み層の特異値の解析（The Singular Values of Convolutional Layers）</news:title>
   <news:publication_date>2026-05-09T19:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688331</loc>
  <lastmod>2026-05-09T19:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地図種類の自動判別における深層畳み込みニューラルネットワークの実用性（Deep Convolutional Neural Networks for Map-Type Classification）</news:title>
   <news:publication_date>2026-05-09T19:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688329</loc>
  <lastmod>2026-05-09T19:12:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師ありディープカーネル学習：予測分散を用いた回帰の実務的示唆 (Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance)</news:title>
   <news:publication_date>2026-05-09T19:12:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688327</loc>
  <lastmod>2026-05-09T18:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できるIoTのための教師なし学習（Unsupervised Learning for Trustworthy IoT）</news:title>
   <news:publication_date>2026-05-09T18:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688325</loc>
  <lastmod>2026-05-09T18:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頭頸部がんに対する3次元放射線治療線量予測の新アーキテクチャ（Three-Dimensional Radiotherapy Dose Prediction on Head and Neck Cancer Patients with a Hierarchically Densely Connected U-net Deep Learning Architecture）</news:title>
   <news:publication_date>2026-05-09T18:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688323</loc>
  <lastmod>2026-05-09T18:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散確率的勾配トラッキング手法の要点（Distributed Stochastic Gradient Tracking Methods）</news:title>
   <news:publication_date>2026-05-09T18:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688321</loc>
  <lastmod>2026-05-09T18:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Reddit AMAにおける質問の有効性の研究（A Study of Question Effectiveness Using Reddit “Ask Me Anything” Threads）</news:title>
   <news:publication_date>2026-05-09T18:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688319</loc>
  <lastmod>2026-05-09T18:19:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>需要変動に反応するコンバージョン率予測（Reacting to Variations in Product Demand: An Application for Conversion Rate (CR) Prediction in Sponsored Search）</news:title>
   <news:publication_date>2026-05-09T18:19:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688317</loc>
  <lastmod>2026-05-09T18:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシーポリシーの曖昧さを機械で読む（Modeling Language Vagueness in Privacy Policies using Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-09T18:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688315</loc>
  <lastmod>2026-05-09T18:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問注目型報酬による強化抽出型要約（Reinforced Extractive Summarization with Question-Focused Rewards）</news:title>
   <news:publication_date>2026-05-09T18:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688313</loc>
  <lastmod>2026-05-09T17:26:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を考慮した大規模距離計量学習（Large-scale Distance Metric Learning with Uncertainty）</news:title>
   <news:publication_date>2026-05-09T17:26:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688311</loc>
  <lastmod>2026-05-09T17:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エルゴディック推論：最適化による収束の加速（Ergodic Inference: Accelerate Convergence by Optimisation）</news:title>
   <news:publication_date>2026-05-09T17:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688309</loc>
  <lastmod>2026-05-09T17:25:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ブロックモデルによる勾配コーディング（Gradient Coding via the Stochastic Block Model）</news:title>
   <news:publication_date>2026-05-09T17:25:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688307</loc>
  <lastmod>2026-05-09T17:25:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない方が強い：腹部超音波画像の同時ビュー分類とランドマーク検出（Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images）</news:title>
   <news:publication_date>2026-05-09T17:25:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688305</loc>
  <lastmod>2026-05-09T17:24:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定な再帰モデルが示す実務的示唆（Stable Recurrent Models）</news:title>
   <news:publication_date>2026-05-09T17:24:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688303</loc>
  <lastmod>2026-05-09T17:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタラーニングで読み解くシンボリック回帰ベンチマークの実態（Analysing Symbolic Regression Benchmarks under a Meta-Learning Approach）</news:title>
   <news:publication_date>2026-05-09T17:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688301</loc>
  <lastmod>2026-05-09T17:24:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロ次の確率的分散削減法が拓くブラックボックス最適化の高速化（Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization）</news:title>
   <news:publication_date>2026-05-09T17:24:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688299</loc>
  <lastmod>2026-05-09T16:33:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対的ネットワークで偽レビューを見抜く（Detecting Deceptive Reviews using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-09T16:33:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688297</loc>
  <lastmod>2026-05-09T16:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Self-Netによる継続学習と自己モデル化の実装（Self-Net: Lifelong Learning via Continual Self-Modeling）</news:title>
   <news:publication_date>2026-05-09T16:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688295</loc>
  <lastmod>2026-05-09T16:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔と体の形状が示す身長推定の可能性（What Face and Body Shapes Can Tell About Height）</news:title>
   <news:publication_date>2026-05-09T16:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688293</loc>
  <lastmod>2026-05-09T16:32:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時非対称テンソル分解の理論的保証（Guaranteed Simultaneous Asymmetric Tensor Decomposition via Orthogonalized Alternating Least Squares）</news:title>
   <news:publication_date>2026-05-09T16:32:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688291</loc>
  <lastmod>2026-05-09T16:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソリアルニューラルネットワークの考え方と実務的意義 (Tensorial Neural Networks: Generalization of Neural Networks and Application to Model Compression)</news:title>
   <news:publication_date>2026-05-09T16:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688289</loc>
  <lastmod>2026-05-09T16:31:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー対応のエンドツーエンドLDA（An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm）</news:title>
   <news:publication_date>2026-05-09T16:31:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688287</loc>
  <lastmod>2026-05-09T16:31:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラム学習による音声感情認識の効率化（Curriculum Learning for Speech Emotion Recognition from Crowdsourced Labels）</news:title>
   <news:publication_date>2026-05-09T16:31:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688285</loc>
  <lastmod>2026-05-09T15:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の意思決定の精度と公平性を高める方法 (Enhancing the Accuracy and Fairness of Human Decision Making)</news:title>
   <news:publication_date>2026-05-09T15:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688283</loc>
  <lastmod>2026-05-09T15:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット双方向機械翻訳（Zero-Shot Dual Machine Translation）</news:title>
   <news:publication_date>2026-05-09T15:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688281</loc>
  <lastmod>2026-05-09T15:30:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字予測におけるアンサンブル学習とオーバーサンプリング（Duluth UROP at SemEval-2018 Task 2: Multilingual Emoji Prediction with Ensemble Learning and Oversampling）</news:title>
   <news:publication_date>2026-05-09T15:30:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688279</loc>
  <lastmod>2026-05-09T15:30:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己模倣による多様な方策の学習（Learning Self-Imitating Diverse Policies）</news:title>
   <news:publication_date>2026-05-09T15:30:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688277</loc>
  <lastmod>2026-05-09T15:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模アジャイル開発における学習の実態（Learning in the Large - An Exploratory Study of Retrospectives in Large-Scale Agile Development）</news:title>
   <news:publication_date>2026-05-09T15:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688275</loc>
  <lastmod>2026-05-09T15:29:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄膜III–V量子ドット太陽電池の光捕捉強化（Light-Trapping Enhanced Thin-Film III-V Quantum Dot Solar Cells Fabricated by Epitaxial Lift-Off）</news:title>
   <news:publication_date>2026-05-09T15:29:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688273</loc>
  <lastmod>2026-05-09T15:28:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天文学における転移学習を用いた銀河合体検出（Using transfer learning to detect galaxy mergers）</news:title>
   <news:publication_date>2026-05-09T15:28:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688271</loc>
  <lastmod>2026-05-09T14:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>起業家と投資家のマッチングツールと研究（Matching Startup Founders to Investors: a Tool and a Study）</news:title>
   <news:publication_date>2026-05-09T14:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688269</loc>
  <lastmod>2026-05-09T14:37:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>影響度最大化による制限付きボルツマンマシンの学習（Learning Restricted Boltzmann Machines via Influence Maximization）</news:title>
   <news:publication_date>2026-05-09T14:37:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688267</loc>
  <lastmod>2026-05-09T14:37:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検証可能な学習者を学習済み検証器で訓練する（Training Verified Learners with Learned Verifiers）</news:title>
   <news:publication_date>2026-05-09T14:37:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688265</loc>
  <lastmod>2026-05-09T14:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模繊維検出と追跡の教師なし学習（Unsupervised Learning for Large-Scale Fiber Detection and Tracking in Microscopic Material Images）</news:title>
   <news:publication_date>2026-05-09T14:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688263</loc>
  <lastmod>2026-05-09T14:36:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列アーキテクチャとハイパーパラメータ探索の効率化（Parallel Architecture and Hyperparameter Search via Successive Halving and Classification）</news:title>
   <news:publication_date>2026-05-09T14:36:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688261</loc>
  <lastmod>2026-05-09T14:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルで頑健なコミュニティ検出（Scalable and Robust Community Detection With Randomized Sketching）</news:title>
   <news:publication_date>2026-05-09T14:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688259</loc>
  <lastmod>2026-05-09T14:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケール空間分解による内在画像変換（Intrinsic Image Transformation via Scale Space Decomposition）</news:title>
   <news:publication_date>2026-05-09T14:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688257</loc>
  <lastmod>2026-05-09T13:45:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どれだけのRestricted Isometryが非凸行列復元に必要か（How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?）</news:title>
   <news:publication_date>2026-05-09T13:45:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688255</loc>
  <lastmod>2026-05-09T13:45:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量注釈で伝播するセグメンテーション（Few-Shot Segmentation Propagation with Guided Networks）</news:title>
   <news:publication_date>2026-05-09T13:45:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688253</loc>
  <lastmod>2026-05-09T13:45:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフオラクルモデル、下界、および並列確率的最適化のギャップ（Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-09T13:45:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688251</loc>
  <lastmod>2026-05-09T13:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変領域分割の実務的進化：SLSDeepの要点と導入観点（SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks）</news:title>
   <news:publication_date>2026-05-09T13:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688249</loc>
  <lastmod>2026-05-09T13:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー学習における重み付き多数決をBregman発散最小化で学ぶ（Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization）</news:title>
   <news:publication_date>2026-05-09T13:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688247</loc>
  <lastmod>2026-05-09T13:44:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COREclust: 複雑データの代表変数を頑健かつスケール可能に選ぶ手法（COREclust: a new package for a robust and scalable analysis of complex data）</news:title>
   <news:publication_date>2026-05-09T13:44:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688245</loc>
  <lastmod>2026-05-09T13:44:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次指示を単一ステップ報酬観測で行動へ対応付ける（Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observation）</news:title>
   <news:publication_date>2026-05-09T13:44:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688243</loc>
  <lastmod>2026-05-09T12:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き生成対向ネットワークによる乳房腫瘤セグメンテーションと形状分類（Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification）</news:title>
   <news:publication_date>2026-05-09T12:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688241</loc>
  <lastmod>2026-05-09T12:52:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情の構造を探るマルチモーダル感情分析（Multimodal Sentiment Analysis To Explore the Structure of Emotions）</news:title>
   <news:publication_date>2026-05-09T12:52:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688239</loc>
  <lastmod>2026-05-09T12:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FastICAにおけるエントロピー推定の落とし穴（On the Estimation of Entropy in the FastICA Algorithm）</news:title>
   <news:publication_date>2026-05-09T12:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688237</loc>
  <lastmod>2026-05-09T12:51:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>獲得関数を最大化する手法（Maximizing acquisition functions for Bayesian optimization）</news:title>
   <news:publication_date>2026-05-09T12:51:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688235</loc>
  <lastmod>2026-05-09T12:51:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算的制約が招く敵対的事例の脆弱性（Adversarial examples from computational constraints）</news:title>
   <news:publication_date>2026-05-09T12:51:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688233</loc>
  <lastmod>2026-05-09T12:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRSIにおける代謝物定量を機械学習で行う意義（Quantification of Metabolites in Magnetic Resonance Spectroscopic Imaging using Machine Learning）</news:title>
   <news:publication_date>2026-05-09T12:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688231</loc>
  <lastmod>2026-05-09T12:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの8ビット学習のためのスケーラブル手法（Scalable Methods for 8-bit Training of Neural Networks）</news:title>
   <news:publication_date>2026-05-09T12:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688229</loc>
  <lastmod>2026-05-09T12:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み型プライバシー重視の音声理解プラットフォーム（Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces）</news:title>
   <news:publication_date>2026-05-09T12:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688227</loc>
  <lastmod>2026-05-09T11:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語→日本語機械翻訳のための再帰型ニューラルネットワークによる事前並べ替え（Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation）</news:title>
   <news:publication_date>2026-05-09T11:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688225</loc>
  <lastmod>2026-05-09T11:58:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別影響推定（Personalized Influence Estimation Technique）</news:title>
   <news:publication_date>2026-05-09T11:58:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688223</loc>
  <lastmod>2026-05-09T11:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ネットワーク埋め込みのスケーラブル手法（Multi-Net: A Scalable Multiplex Network Embedding Framework）</news:title>
   <news:publication_date>2026-05-09T11:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688221</loc>
  <lastmod>2026-05-09T11:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタマテリアルの逆設計を自動化する生成モデル（A Generative Model for Inverse Design of Metamaterials）</news:title>
   <news:publication_date>2026-05-09T11:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688219</loc>
  <lastmod>2026-05-09T11:57:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッド注意ネットワークによるセマンティックセグメンテーションの改善（Pyramid Attention Network for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-09T11:57:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688217</loc>
  <lastmod>2026-05-09T11:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯学習的アプローチによる脳MRIセグメンテーションの横断的適応（A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols）</news:title>
   <news:publication_date>2026-05-09T11:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688215</loc>
  <lastmod>2026-05-09T11:05:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的参照フレームを用いた予測窓の創出（Futuristic Classification with Dynamic Reference Frame Strategy）</news:title>
   <news:publication_date>2026-05-09T11:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688213</loc>
  <lastmod>2026-05-09T11:05:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮するニューラル機械翻訳が照応解析（anaphora resolution）を学習する仕組み（Context-Aware Neural Machine Translation Learns Anaphora Resolution）</news:title>
   <news:publication_date>2026-05-09T11:05:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688211</loc>
  <lastmod>2026-05-09T11:05:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Airbnbの新規掲載物件の価格予測手法（Unravelling Airbnb: Predicting Price for New Listing）</news:title>
   <news:publication_date>2026-05-09T11:05:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688209</loc>
  <lastmod>2026-05-09T11:04:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非調和キャビティQED領域における分子オプトメカニクス（Molecular optomechanics in the anharmonic cavity-QED regime using hybrid metal-dielectric cavity modes）</news:title>
   <news:publication_date>2026-05-09T11:04:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688207</loc>
  <lastmod>2026-05-09T11:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を統計モデルに組み込む新手法：DeepGLMとDeepGLMM（Bayesian Deep Net GLM and GLMM）</news:title>
   <news:publication_date>2026-05-09T11:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688205</loc>
  <lastmod>2026-05-09T11:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体志向の動的予測モデルが示した一般化の道（Object-Oriented Dynamics Predictor）</news:title>
   <news:publication_date>2026-05-09T11:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688203</loc>
  <lastmod>2026-05-09T11:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的推論で答えるAI：仮想イメージによる質問応答（Think Visually: Question Answering through Virtual Imagery）</news:title>
   <news:publication_date>2026-05-09T11:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688201</loc>
  <lastmod>2026-05-09T10:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信効率を劇的に下げる二重量子化（Double Quantization for Communication-Efﬁcient Distributed Optimization）</news:title>
   <news:publication_date>2026-05-09T10:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688199</loc>
  <lastmod>2026-05-09T10:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Relation Networksを用いたソース表現の洗練（Refining Source Representations with Relation Networks for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-09T10:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688197</loc>
  <lastmod>2026-05-09T10:10:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補間から回帰へ：再構成アプローチ（The Reconstruction Approach: From Interpolation to Regression）</news:title>
   <news:publication_date>2026-05-09T10:10:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688195</loc>
  <lastmod>2026-05-09T10:09:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダブルディープ・スパシオアングラー学習によるライトフィールド顔認識（Double-Deep Spatio-Angular Learning for Light Field Based Face Recognition）</news:title>
   <news:publication_date>2026-05-09T10:09:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688193</loc>
  <lastmod>2026-05-09T10:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数パスを用いた確率的勾配降下法の統計的最適性（Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes）</news:title>
   <news:publication_date>2026-05-09T10:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688191</loc>
  <lastmod>2026-05-09T10:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欧州通貨統合の歴史から学ぶ教訓（Lessons from the History of European EMU）</news:title>
   <news:publication_date>2026-05-09T10:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688189</loc>
  <lastmod>2026-05-09T10:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中魚種分類における畳み込みニューラルネットワークと深層学習（Underwater Fish Species Classification using Convolutional Neural Network and Deep Learning）</news:title>
   <news:publication_date>2026-05-09T10:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688187</loc>
  <lastmod>2026-05-09T09:16:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化する環境下で学習するスライディングウィンドウ手法（A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions）</news:title>
   <news:publication_date>2026-05-09T09:16:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688185</loc>
  <lastmod>2026-05-09T09:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイラル銀河NGC 1560の恒星ハローの検出（THE STELLAR HALO OF THE SPIRAL GALAXY NGC 1560）</news:title>
   <news:publication_date>2026-05-09T09:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688183</loc>
  <lastmod>2026-05-09T09:16:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模多変量オーンシュタイン＝ウーレンベック脳結合のベイズ推定（Bayesian estimation for large scale multivariate Ornstein-Uhlenbeck model of brain connectivity）</news:title>
   <news:publication_date>2026-05-09T09:16:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688181</loc>
  <lastmod>2026-05-09T09:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的手法で降下保証を与えるICAアルゴリズム（Stochastic algorithms with descent guarantees for ICA）</news:title>
   <news:publication_date>2026-05-09T09:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688179</loc>
  <lastmod>2026-05-09T09:16:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再構成可能なテラヘルツ四分の一波長板によるヘリシティ切替（Reconfigurable terahertz quarter-wave plate for helicity switching based on Babinet inversion of anisotropic checkerboard metasurface）</news:title>
   <news:publication_date>2026-05-09T09:16:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688177</loc>
  <lastmod>2026-05-09T09:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造役割を保つネットワーク埋め込み（struc2gauss: Structural Role Preserving Network Embedding via Gaussian Embedding）</news:title>
   <news:publication_date>2026-05-09T09:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688175</loc>
  <lastmod>2026-05-09T09:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ユニット状態認識のためのマルチチャネルデータ融合（Learning Unit State Recognition Based on Multi-channel Data Fusion）</news:title>
   <news:publication_date>2026-05-09T09:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688173</loc>
  <lastmod>2026-05-09T08:24:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zenoによる分散SGDの疑いベース耐故障性（Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance）</news:title>
   <news:publication_date>2026-05-09T08:24:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688171</loc>
  <lastmod>2026-05-09T08:24:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>酩酊顔のデータセットによる酔っぱらい検知（DIF: Dataset of Perceived Intoxicated Faces for Drunk Person Identification）</news:title>
   <news:publication_date>2026-05-09T08:24:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688169</loc>
  <lastmod>2026-05-09T08:24:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電気生理モデルの応答面が不連続な場合のガウス過程エミュレーション（Gaussian process emulation for discontinuous response surfaces with applications for cardiac electrophysiology models）</news:title>
   <news:publication_date>2026-05-09T08:24:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688167</loc>
  <lastmod>2026-05-09T08:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル伝搬を学習する：少数ショット学習のための推論ネットワーク（Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning）</news:title>
   <news:publication_date>2026-05-09T08:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688165</loc>
  <lastmod>2026-05-09T08:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序付き近傍グラフのカーネル（KONG: Kernels for ordered-neighborhood graphs）</news:title>
   <news:publication_date>2026-05-09T08:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688163</loc>
  <lastmod>2026-05-09T08:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム射影と適格トレースを組み合わせたLSTDの有限サンプル解析（Finite Sample Analysis of LSTD with Random Projections and Eligibility Traces）</news:title>
   <news:publication_date>2026-05-09T08:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688161</loc>
  <lastmod>2026-05-09T08:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境音分類のためのマスク付き条件付きニューラルネットワーク（Masked Conditional Neural Networks for Environmental Sound Classification）</news:title>
   <news:publication_date>2026-05-09T08:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/688159</loc>
  <lastmod>2026-05-09T07:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SOSAによるセンサー観測の軽量語彙（SOSA: A Lightweight Ontology for Sensors, Observations, Samples, and Actuators）</news:title>
   <news:publication_date>2026-05-09T07:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/688157</loc>
  <lastmod>2026-05-09T07:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Virtual-Taobaoによる仮想化学習基盤の事業的インパクト（Virtual-Taobao: Virtualizing Real-world Online Retail Environment for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-09T07:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/688155</loc>
  <lastmod>2026-05-09T07:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライフロングドメイン単語埋め込みとメタラーニング（Lifelong Domain Word Embedding via Meta-Learning）</news:title>
   <news:publication_date>2026-05-09T07:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/688153</loc>
  <lastmod>2026-05-09T07:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習に基づく安全な最適経路計画（Safe learning-based optimal motion planning for automated driving）</news:title>
   <news:publication_date>2026-05-09T07:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688151</loc>
  <lastmod>2026-05-09T07:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムビニング特徴を用いた大規模スペクトルクラスタリングの高速化（Scalable Spectral Clustering Using Random Binning Features）</news:title>
   <news:publication_date>2026-05-09T07:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688149</loc>
  <lastmod>2026-05-09T07:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン芸術画像から学ぶ任意のスタイル転送（Learning from Multi-domain Artistic Images for Arbitrary Style Transfer）</news:title>
   <news:publication_date>2026-05-09T07:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688147</loc>
  <lastmod>2026-05-09T07:21:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフの“翻訳”で稀な事象を予測する（Deep Graph Translation）</news:title>
   <news:publication_date>2026-05-09T07:21:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688145</loc>
  <lastmod>2026-05-09T06:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散Cartesianべきグラフ分割によるグラフオン推定（Distributed Cartesian Power Graph Segmentation for Graphon Estimation）</news:title>
   <news:publication_date>2026-05-09T06:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688143</loc>
  <lastmod>2026-05-09T06:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分パートに基づく構造的サポート相関フィルタによる視覚追跡（Part-based Visual Tracking via Structural Support Correlation Filter）</news:title>
   <news:publication_date>2026-05-09T06:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688141</loc>
  <lastmod>2026-05-09T06:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体的報酬によるリスク回避型強化学習（Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards）</news:title>
   <news:publication_date>2026-05-09T06:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688139</loc>
  <lastmod>2026-05-09T06:29:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信効率化のための遅延集約勾配（Lazily Aggregated Gradient: LAG）</news:title>
   <news:publication_date>2026-05-09T06:29:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688137</loc>
  <lastmod>2026-05-09T06:29:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>より効率的な確率的分散学習：収束の高速化とスパース通信（Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication）</news:title>
   <news:publication_date>2026-05-09T06:29:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688135</loc>
  <lastmod>2026-05-09T06:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事後サンプリングに基づくミオピック実験設計（Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming）</news:title>
   <news:publication_date>2026-05-09T06:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688133</loc>
  <lastmod>2026-05-09T06:28:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>調理状態認識のためのInceptionアーキテクチャ応用（Cooking State Recognition from Images Using Inception Architecture）</news:title>
   <news:publication_date>2026-05-09T06:28:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688131</loc>
  <lastmod>2026-05-09T05:37:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Meta Transfer Learning for Facial Emotion Recognition（Meta Transfer Learning for Facial Emotion Recognition）</news:title>
   <news:publication_date>2026-05-09T05:37:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688129</loc>
  <lastmod>2026-05-09T05:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層機能辞書による3Dモデルの一貫した意味構造学習（Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions）</news:title>
   <news:publication_date>2026-05-09T05:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688127</loc>
  <lastmod>2026-05-09T05:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitter上の乳がん治療経験の感情分析が示すもの（A Sentiment Analysis of Breast Cancer Treatment Experiences and Healthcare Perceptions Across Twitter）</news:title>
   <news:publication_date>2026-05-09T05:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688125</loc>
  <lastmod>2026-05-09T05:36:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復停止による非パラメトリック検定の最適化（Early Stopping for Nonparametric Testing）</news:title>
   <news:publication_date>2026-05-09T05:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688123</loc>
  <lastmod>2026-05-09T05:36:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定境界のトポロジカルデータ解析（Topological Data Analysis of Decision Boundaries with Application to Model Selection）</news:title>
   <news:publication_date>2026-05-09T05:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688121</loc>
  <lastmod>2026-05-09T05:36:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヤンヤン地下研究所での高感度アルファ粒子検出器の初期性能（Initial performance of the high sensitivity alpha particle detector at the Yangyang underground laboratory）</news:title>
   <news:publication_date>2026-05-09T05:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688119</loc>
  <lastmod>2026-05-09T05:36:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列計算で使える機械数の限界（How Many Machines Can We Use in Parallel Computing for Kernel Ridge Regression?）</news:title>
   <news:publication_date>2026-05-09T05:36:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688117</loc>
  <lastmod>2026-05-09T04:45:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Polynomially Coded Regressionによるストラグラー対策と分散学習の効率化（Polynomially Coded Regression: Optimal Straggler Mitigation via Data Encoding）</news:title>
   <news:publication_date>2026-05-09T04:45:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688115</loc>
  <lastmod>2026-05-09T04:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトニックニューラルネットワークの現場学習法（Training of photonic neural networks through in situ backpropagation）</news:title>
   <news:publication_date>2026-05-09T04:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688113</loc>
  <lastmod>2026-05-09T04:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの自動検証—安全性を担保するための現状と展望（Automated Verification of Neural Networks: Advances, Challenges and Perspectives）</news:title>
   <news:publication_date>2026-05-09T04:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688111</loc>
  <lastmod>2026-05-09T04:43:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フェルミオン-ボソン相互作用系のデジタル量子計算（Digital quantum computation of fermion-boson interacting systems）</news:title>
   <news:publication_date>2026-05-09T04:43:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688109</loc>
  <lastmod>2026-05-09T04:42:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測のための確率的推論をメタ学習する枠組み（Meta-Learning Probabilistic Inference for Prediction）</news:title>
   <news:publication_date>2026-05-09T04:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688107</loc>
  <lastmod>2026-05-09T04:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな遠隔教師あり学習による関係抽出の強化（Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-09T04:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688105</loc>
  <lastmod>2026-05-09T04:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DSGANに学ぶ遠隔監督(Relation Extraction)のノイズ対処（DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction）</news:title>
   <news:publication_date>2026-05-09T04:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688103</loc>
  <lastmod>2026-05-09T03:51:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスクDPPを活用した推薦の本質（Multi-Task Determinantal Point Processes for Recommendation）</news:title>
   <news:publication_date>2026-05-09T03:51:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688101</loc>
  <lastmod>2026-05-09T03:50:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fairness GANによる公平なデータ生成（Fairness GAN）</news:title>
   <news:publication_date>2026-05-09T03:50:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688099</loc>
  <lastmod>2026-05-09T03:49:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列からの構造学習と誤検出制御 (Structure Learning from Time Series with False Discovery Control)</news:title>
   <news:publication_date>2026-05-09T03:49:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688097</loc>
  <lastmod>2026-05-09T03:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト結合ネットワークの拡張：Diffusion Mapsによる埋め込み（Diffusion Maps for Textual Network Embedding）</news:title>
   <news:publication_date>2026-05-09T03:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688095</loc>
  <lastmod>2026-05-09T03:48:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>列生成によるブール決定ルール学習（Boolean Decision Rules via Column Generation）</news:title>
   <news:publication_date>2026-05-09T03:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688093</loc>
  <lastmod>2026-05-09T03:47:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VIPERSによる銀河分類の再定義（The VIMOS Public Extragalactic Redshift Survey: The complexity of galaxy populations revealed with unsupervised machine-learning algorithms）</news:title>
   <news:publication_date>2026-05-09T03:47:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688091</loc>
  <lastmod>2026-05-09T03:47:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所H0測定における宇宙分散の影響（The impact of the cosmic variance on H0 on cosmological analyses）</news:title>
   <news:publication_date>2026-05-09T03:47:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688089</loc>
  <lastmod>2026-05-09T02:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共通メンバーシップ攻撃（Co-Membership Attacks）に関する解説</news:title>
   <news:publication_date>2026-05-09T02:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688087</loc>
  <lastmod>2026-05-09T02:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルシウムイメージングから学ぶ脳活動の動力学：結合van der PolとLSTMのハイブリッド（Learning Brain Dynamics from Calcium Imaging with Coupled van der Pol and LSTM）</news:title>
   <news:publication_date>2026-05-09T02:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688085</loc>
  <lastmod>2026-05-09T02:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク行列回帰における特異部分空間の信頼領域（Confidence Region of Singular Subspaces for Low-rank Matrix Regression）</news:title>
   <news:publication_date>2026-05-09T02:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688083</loc>
  <lastmod>2026-05-09T02:54:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反事実的公平性の下での因果モデルの統合（Pooling of Causal Models under Counterfactual Fairness via Causal Judgement Aggregation）</news:title>
   <news:publication_date>2026-05-09T02:54:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688081</loc>
  <lastmod>2026-05-09T02:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学力分布を用いた教育格差の可視化（Measure of gap and inequalities in basic education students proficiencies）</news:title>
   <news:publication_date>2026-05-09T02:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688079</loc>
  <lastmod>2026-05-09T02:54:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速ニューラル機械翻訳の実装手法（Fast Neural Machine Translation Implementation）</news:title>
   <news:publication_date>2026-05-09T02:54:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688077</loc>
  <lastmod>2026-05-09T02:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動から読み解く「内部モデル」の推定法（Inverse Rational Control: Inferring What You Think from How You Forage）</news:title>
   <news:publication_date>2026-05-09T02:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688075</loc>
  <lastmod>2026-05-09T02:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>z≈3の双AGN系の宿主銀河を捉える — HAWK-I+GRAALによる観測の重要性（A cosmic dance at z ∼3: Detecting the host galaxies of the dual AGN system LBQS 0302−0019 and Jil with HAWK-I+GRAAL）</news:title>
   <news:publication_date>2026-05-09T02:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688073</loc>
  <lastmod>2026-05-09T02:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H I自己吸収（HISA）温度の較正とリーゲル–クラッチャー雲の温度測定（Calibrating the HISA temperature: Measuring the temperature of the Riegel–Crutcher cloud）</news:title>
   <news:publication_date>2026-05-09T02:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688071</loc>
  <lastmod>2026-05-09T02:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の温暖中性中間層のHI 21cm吸収による検出 (Detection of the Galactic Warm Neutral Medium in HI 21cm absorption)</news:title>
   <news:publication_date>2026-05-09T02:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688069</loc>
  <lastmod>2026-05-09T02:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステレオ拡大：マルチプレーン画像を用いたビュー合成学習（Stereo Magnification: Learning view synthesis using multiplane images）</news:title>
   <news:publication_date>2026-05-09T02:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688067</loc>
  <lastmod>2026-05-09T01:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純語埋め込みモデルの再評価（Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms）</news:title>
   <news:publication_date>2026-05-09T01:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688065</loc>
  <lastmod>2026-05-09T01:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Competitive Collaborationによる無監督での深度・カメラ動作・オプティカルフロー・動き分割の同時学習（Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation）</news:title>
   <news:publication_date>2026-05-09T01:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688063</loc>
  <lastmod>2026-05-09T01:59:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レッドシフト広帯吸収線クエーサーの機械学習による発見（Redshifted broad absorption line quasars found via machine-learned spectral similarity）</news:title>
   <news:publication_date>2026-05-09T01:59:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688061</loc>
  <lastmod>2026-05-09T01:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタグラディエント強化学習の要点（Meta-Gradient Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-09T01:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688059</loc>
  <lastmod>2026-05-09T01:07:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基礎fMRIから自閉症治療反応を予測する手法（Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging）</news:title>
   <news:publication_date>2026-05-09T01:07:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688057</loc>
  <lastmod>2026-05-09T01:07:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Implicit Autoencoders（Implicit Autoencoders）</news:title>
   <news:publication_date>2026-05-09T01:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688055</loc>
  <lastmod>2026-05-09T01:06:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光浸漬（Light Soaking）でJSCが低下する原因：EV+0.98 eVトラップの役割（Role of EV+0.98 eV trap in light soaking-induced short circuit current instability in CIGS solar cells）</news:title>
   <news:publication_date>2026-05-09T01:06:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688053</loc>
  <lastmod>2026-05-09T01:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レイヤー単位のニューロン共有によるマルチタスク圧縮（Multi-Task Zipping via Layer-wise Neuron Sharing）</news:title>
   <news:publication_date>2026-05-09T01:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688051</loc>
  <lastmod>2026-05-09T01:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層性を活かす注意機構の再定義：Hyperbolic Attention Networks（Hyperbolic Attention Networks）</news:title>
   <news:publication_date>2026-05-09T01:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688049</loc>
  <lastmod>2026-05-09T01:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンディット問題におけるブートストラップの新知見（New Insights into Bootstrapping for Bandits）</news:title>
   <news:publication_date>2026-05-09T01:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688047</loc>
  <lastmod>2026-05-09T00:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおけるエントロピーと相互情報量の定量化（Entropy and mutual information in models of deep neural networks）</news:title>
   <news:publication_date>2026-05-09T00:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688045</loc>
  <lastmod>2026-05-09T00:03:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>技術サポート文書から手順を抽出する方法（Mining Procedures from Technical Support Documents）</news:title>
   <news:publication_date>2026-05-09T00:03:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688043</loc>
  <lastmod>2026-05-09T00:03:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多タスク・コックス過程における効率的推論（Efficient Inference in Multi-task Cox Process Models）</news:title>
   <news:publication_date>2026-05-09T00:03:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688041</loc>
  <lastmod>2026-05-09T00:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Local SGDによる分散学習の通信最適化（Local SGD Converges Fast and Communicates Little）</news:title>
   <news:publication_date>2026-05-09T00:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688039</loc>
  <lastmod>2026-05-09T00:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ時間分解能とマルチレベル特徴を組み合わせた環境音分類（Environmental Sound Classification Based on Multi-temporal Resolution Convolutional Neural Network Combining with Multi-level Features）</news:title>
   <news:publication_date>2026-05-09T00:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688037</loc>
  <lastmod>2026-05-09T00:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精密なスパイク時刻を用いた学習：Liquid State Machineの新しいデコーディングアルゴリズム（Learning with precise spike times: A new decoding algorithm for liquid state machines）</news:title>
   <news:publication_date>2026-05-09T00:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688035</loc>
  <lastmod>2026-05-09T00:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理的Hidden Markov Treeによる洪水範囲推定（Geographical Hidden Markov Tree for Flood Extent Mapping）</news:title>
   <news:publication_date>2026-05-09T00:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688033</loc>
  <lastmod>2026-05-08T23:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MobiFace：モバイル環境における顔追跡のための大規模データセット（MobiFace: A Novel Dataset for Mobile Face Tracking in the Wild）</news:title>
   <news:publication_date>2026-05-08T23:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688031</loc>
  <lastmod>2026-05-08T23:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同字異形文字（Homoglyph）攻撃の検出に関するSiameseニューラルネットワークの提案（Detecting Homoglyph Attacks with a Siamese Neural Network）</news:title>
   <news:publication_date>2026-05-08T23:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688029</loc>
  <lastmod>2026-05-08T23:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習評価の再設計がもたらす本質的な変化（Towards Robust Evaluations of Continual Learning）</news:title>
   <news:publication_date>2026-05-08T23:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688027</loc>
  <lastmod>2026-05-08T23:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fenchel-Young損失による分類器学習の新枠組み（Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms）</news:title>
   <news:publication_date>2026-05-08T23:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688025</loc>
  <lastmod>2026-05-08T23:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン分離のための画像間翻訳（Image-to-image translation for cross-domain disentanglement）</news:title>
   <news:publication_date>2026-05-08T23:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688023</loc>
  <lastmod>2026-05-08T23:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マージン付きデータからの凸多面体学習（Learning convex polyhedra with margin*）</news:title>
   <news:publication_date>2026-05-08T23:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688021</loc>
  <lastmod>2026-05-08T23:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所近似による動的システムの効率的符号化（Efficient Encoding of Dynamical Systems through Local Approximations）</news:title>
   <news:publication_date>2026-05-08T23:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688019</loc>
  <lastmod>2026-05-08T22:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによる深層ニューラルネットワークのパラメータ同時自動最適化（Autonomously and Simultaneously Refining Deep Neural Network Parameters by Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-08T22:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688017</loc>
  <lastmod>2026-05-08T22:16:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的関係事実学習によるVQA改善（R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering）</news:title>
   <news:publication_date>2026-05-08T22:16:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688015</loc>
  <lastmod>2026-05-08T22:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張と学習を同時最適化する手法（Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation）</news:title>
   <news:publication_date>2026-05-08T22:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688013</loc>
  <lastmod>2026-05-08T22:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全結合再構成層を持つ深層残差ネットワークによる単一画像超解像（Deep Residual Networks with a Fully Connected Reconstruction Layer for Single Image Super-Resolution）</news:title>
   <news:publication_date>2026-05-08T22:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688011</loc>
  <lastmod>2026-05-08T22:14:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Interventionによる因果モデルの学習と検証（Learning and Testing Causal Models with Interventions）</news:title>
   <news:publication_date>2026-05-08T22:14:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688009</loc>
  <lastmod>2026-05-08T22:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタラーニングとエピソディックリコールが切り開く再発タスクの学習（Meta-Learning with Episodic Recall）</news:title>
   <news:publication_date>2026-05-08T22:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688007</loc>
  <lastmod>2026-05-08T22:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的辞書学習によるGPR地雷分類の高速化と実地適応（Dictionary Learning for Adaptive GPR Landmine Classification）</news:title>
   <news:publication_date>2026-05-08T22:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688005</loc>
  <lastmod>2026-05-08T21:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IDEASによるセキュリティ分析の再設計（Forming IDEAS: Interactive Data Exploration &amp;amp; Analysis System – Configurable Visual Analytics for Cyber Security Analysts）</news:title>
   <news:publication_date>2026-05-08T21:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688003</loc>
  <lastmod>2026-05-08T21:21:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LF-Netによる局所特徴学習（LF-Net: Learning Local Features from Images）</news:title>
   <news:publication_date>2026-05-08T21:21:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/688001</loc>
  <lastmod>2026-05-08T21:21:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電磁脳信号のための多変量畳み込みスパースコーディング（Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals）</news:title>
   <news:publication_date>2026-05-08T21:21:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687999</loc>
  <lastmod>2026-05-08T21:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Regularized Nonlinear Acceleration の要点と実務への示唆（Online Regularized Nonlinear Acceleration）</news:title>
   <news:publication_date>2026-05-08T21:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687997</loc>
  <lastmod>2026-05-08T21:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異文化が出会うとき――クロスカルチュラル・ナレッジスペースの設計（When Cultures Meet: Modelling Cross-Cultural Knowledge Spaces）</news:title>
   <news:publication_date>2026-05-08T21:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687995</loc>
  <lastmod>2026-05-08T21:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合マルチリンガル空間での平行データのフィルタリングと抽出（Filtering and Mining Parallel Data in a Joint Multilingual Space）</news:title>
   <news:publication_date>2026-05-08T21:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687993</loc>
  <lastmod>2026-05-08T21:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を考慮した注意機構による信頼性向上（Uncertainty-Aware Attention for Reliable Interpretation and Prediction）</news:title>
   <news:publication_date>2026-05-08T21:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687991</loc>
  <lastmod>2026-05-08T20:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線共存管理における強化学習ベースの資源配分（Resource Allocation for a Wireless Coexistence Management System Based on Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-08T20:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687989</loc>
  <lastmod>2026-05-08T20:27:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習中の干渉と前進の一歩（One step back, two steps forward: interference and learning in recurrent neural networks）</news:title>
   <news:publication_date>2026-05-08T20:27:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687987</loc>
  <lastmod>2026-05-08T20:27:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SOSELETOによる転移学習とノイズラベル対策の統一的アプローチ（SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels）</news:title>
   <news:publication_date>2026-05-08T20:27:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687985</loc>
  <lastmod>2026-05-08T20:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>N次元ベクトルニューロンの汎用バックプロパゲーション（Backpropagation with N-D Vector-Valued Neurons Using Arbitrary Bilinear Products）</news:title>
   <news:publication_date>2026-05-08T20:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687983</loc>
  <lastmod>2026-05-08T20:26:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入門プログラミングにおける問題類似度の測定（Measuring Item Similarity in Introductory Programming: Python and Robot Programming Case Studies）</news:title>
   <news:publication_date>2026-05-08T20:26:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687981</loc>
  <lastmod>2026-05-08T20:25:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual Networksを「変形の流れ」として読む — ResNetと微分同相写像の関係（Residual Networks as Geodesic Flows of Diffeomorphisms）</news:title>
   <news:publication_date>2026-05-08T20:25:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687979</loc>
  <lastmod>2026-05-08T20:25:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続行動空間におけるAlpha Zeroの拡張（A0C: Alpha Zero in Continuous Action Space）</news:title>
   <news:publication_date>2026-05-08T20:25:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687977</loc>
  <lastmod>2026-05-08T19:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偶然の深宇宙観測領域バイアスが示す注意点（Accidental deep field bias in CMB T and SNe z correlation）</news:title>
   <news:publication_date>2026-05-08T19:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687975</loc>
  <lastmod>2026-05-08T19:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>酸化物界面における絶縁状態の渦励起（Vortex excitations in the Insulating State of an Oxide Interface）</news:title>
   <news:publication_date>2026-05-08T19:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687973</loc>
  <lastmod>2026-05-08T19:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Primal-Dual Wasserstein GANの要点と事業活用の示唆（Primal-Dual Wasserstein GAN）</news:title>
   <news:publication_date>2026-05-08T19:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687971</loc>
  <lastmod>2026-05-08T19:32:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模論文・技術文書を機械的に読み解く仕組み（Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale）</news:title>
   <news:publication_date>2026-05-08T19:32:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687969</loc>
  <lastmod>2026-05-08T19:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>System APIに基づくAndroidランサムウェア検出の有効性（On the Effectiveness of System API-Related Information for Android Ransomware Detection）</news:title>
   <news:publication_date>2026-05-08T19:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687967</loc>
  <lastmod>2026-05-08T19:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関連学習における可解釈性と合成性を高める共同訓練型オートエンコーダ（Interpretable and Compositional Relation Learning by Joint Training with an Autoencoder）</news:title>
   <news:publication_date>2026-05-08T19:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687965</loc>
  <lastmod>2026-05-08T19:31:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在因子とその結合性を同時に学習する統一確率モデル（A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data）</news:title>
   <news:publication_date>2026-05-08T19:31:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687963</loc>
  <lastmod>2026-05-08T18:39:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたECEIデータ前処理：機械学習による異常信号の自動識別（An Automatic Data Cleaning Procedure for Electron Cyclotron Emission Imaging on EAST Tokamak Using Machine Learning Algorithm）</news:title>
   <news:publication_date>2026-05-08T18:39:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687961</loc>
  <lastmod>2026-05-08T18:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適輸送を用いた過剰パラメータ化モデルの勾配降下法の大域収束（On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport）</news:title>
   <news:publication_date>2026-05-08T18:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687959</loc>
  <lastmod>2026-05-08T18:39:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AVIDによる視覚的異常検知の敵対的学習（Adversarial Visual Irregularity Detection）</news:title>
   <news:publication_date>2026-05-08T18:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687957</loc>
  <lastmod>2026-05-08T18:37:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Laplacian Networks：ニューラルネットワークにおけるクラス境界の平滑化を制御する正則化（Laplacian Networks: Bounding Indicator Function Smoothness for Neural Networks）</news:title>
   <news:publication_date>2026-05-08T18:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687955</loc>
  <lastmod>2026-05-08T18:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタッキングによる分子原子化エネルギー予測の精度改善（Stacked Generalization Approach to Improve Prediction of Molecular Atomization Energies）</news:title>
   <news:publication_date>2026-05-08T18:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687953</loc>
  <lastmod>2026-05-08T18:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数を扱う安定化仕様探索法（Stable specification search in structural equation model with latent variables）</news:title>
   <news:publication_date>2026-05-08T18:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687951</loc>
  <lastmod>2026-05-08T18:35:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像に対する高速多段階物体検出の手法（You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery）</news:title>
   <news:publication_date>2026-05-08T18:35:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687949</loc>
  <lastmod>2026-05-08T17:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ中の単一コミュニティ探索（Searching for a Single Community in a Graph）</news:title>
   <news:publication_date>2026-05-08T17:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687947</loc>
  <lastmod>2026-05-08T17:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KNOB-SynC: 非パラメトリック重複度に基づくシンシティアルクラスタリング（Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering）</news:title>
   <news:publication_date>2026-05-08T17:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687945</loc>
  <lastmod>2026-05-08T17:42:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張ポリシーの自動探索（AutoAugment: Learning Augmentation Strategies from Data）</news:title>
   <news:publication_date>2026-05-08T17:42:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687943</loc>
  <lastmod>2026-05-08T17:42:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VisemeNet: 音声駆動のアニメーター向けスピーチアニメーション（VisemeNet: Audio-Driven Animator-Centric Speech Animation）</news:title>
   <news:publication_date>2026-05-08T17:42:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/687941</loc>
  <lastmod>2026-05-08T17:41:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的アドバイザベースアンサンブル（Dynamic Advisor-Based Ensemble (dynABE): Case study in stock trend prediction of critical metal companies）</news:title>
   <news:publication_date>2026-05-08T17:41:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687939</loc>
  <lastmod>2026-05-08T17:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散クラスタリングと外れ値検出の実務的アルゴリズム（A Practical Algorithm for Distributed Clustering and Outlier Detection）</news:title>
   <news:publication_date>2026-05-08T17:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687937</loc>
  <lastmod>2026-05-08T17:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間探索と敵対的損失によるクロスドメイン画像生成（Cross Domain Image Generation through Latent Space Exploration with Adversarial Loss）</news:title>
   <news:publication_date>2026-05-08T17:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687935</loc>
  <lastmod>2026-05-08T16:49:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>なぜジョニーはパスワードを安全に保存できないのか（Why Johnny Can’t Store Passwords Securely? A Usability Evaluation of Bouncycastle Password Hashing）</news:title>
   <news:publication_date>2026-05-08T16:49:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687933</loc>
  <lastmod>2026-05-08T16:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレベル深層カスケード木によるCVR予測（Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System）</news:title>
   <news:publication_date>2026-05-08T16:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687931</loc>
  <lastmod>2026-05-08T16:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続型非単調サブモジュラ最適化の最適アルゴリズム（Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization）</news:title>
   <news:publication_date>2026-05-08T16:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687929</loc>
  <lastmod>2026-05-08T16:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リソース制約下のIoTで大規模DNNを動かすローカル量子化（Deploy Large-Scale Deep Neural Networks in Resource Constrained IoT Devices with Local Quantization Region）</news:title>
   <news:publication_date>2026-05-08T16:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687927</loc>
  <lastmod>2026-05-08T16:48:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VisualBackPropを用いた学習における特権情報の活用（VisualBackProp for learning using privileged information with CNNs）</news:title>
   <news:publication_date>2026-05-08T16:48:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687925</loc>
  <lastmod>2026-05-08T16:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造制約付き階層クラスタリング（Hierarchical Clustering with Structural Constraints）</news:title>
   <news:publication_date>2026-05-08T16:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687923</loc>
  <lastmod>2026-05-08T16:47:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸学習における非同期SGDの収束を制御する手法（Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning）</news:title>
   <news:publication_date>2026-05-08T16:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687921</loc>
  <lastmod>2026-05-08T15:56:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントリーワイズℓpノルム低ランク近似の実用的アルゴリズム（Simple and practical algorithms for ℓp-norm low-rank approximation）</news:title>
   <news:publication_date>2026-05-08T15:56:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687919</loc>
  <lastmod>2026-05-08T15:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詳細な部品分割のための複雑な関係を組み込んだ深層構造予測モデル（Complex Relations in a Deep Structured Prediction Model for Fine Image Segmentation）</news:title>
   <news:publication_date>2026-05-08T15:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687917</loc>
  <lastmod>2026-05-08T15:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Reinforcement Learningを用いたSeq2Seqモデルの強化（Deep Reinforcement Learning for Sequence-to-Sequence Models）</news:title>
   <news:publication_date>2026-05-08T15:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687915</loc>
  <lastmod>2026-05-08T15:54:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフとゼロノイズ極限に関する半教師付き学習の理論的限界（LARGE DATA AND ZERO NOISE LIMITS OF GRAPH-BASED SEMI-SUPERVISED LEARNING ALGORITHMS）</news:title>
   <news:publication_date>2026-05-08T15:54:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687913</loc>
  <lastmod>2026-05-08T15:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴に基づく生成モデルを用いたDyna計画（Dyna Planning using a Feature Based Generative Model）</news:title>
   <news:publication_date>2026-05-08T15:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687911</loc>
  <lastmod>2026-05-08T15:54:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不変表現と敵対的学習を超える情報理論的アプローチ（Invariant Representations without Adversarial Training）</news:title>
   <news:publication_date>2026-05-08T15:54:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687909</loc>
  <lastmod>2026-05-08T15:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慎重な深層学習（Cautious Deep Learning）</news:title>
   <news:publication_date>2026-05-08T15:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/687907</loc>
  <lastmod>2026-05-08T15:02:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二段階部分空間トラストリージョンによる深層ニューラルネットの訓練（A Two-Stage Subspace Trust Region Approach for Deep Neural Network Training）</news:title>
   <news:publication_date>2026-05-08T15:02:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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