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   <news:title>オンライン非凸学習におけるFTPLの最適性（Online Non-Convex Learning: Following the Perturbed Leader is Optimal）</news:title>
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   <news:title>大規模MIMOにおける合計スペクトル効率最大化（Sum Spectral Efficiency Maximization in Massive MIMO Systems: Benefits from Deep Learning）</news:title>
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   <news:title>隠れた自己エネルギーが高温超伝導を生む（Hidden self-energies as origin of cuprate superconductivity revealed by machine learning）</news:title>
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   <news:title>イベント駆動パルス制御と必要時のモデル学習（Event-triggered Pulse Control with Model Learning (if Necessary))</news:title>
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   <news:title>IndyLSTMs：独立再帰型LSTM（Independently Recurrent LSTMs）</news:title>
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   <news:title>小惑星族の分類学的研究（A Taxonomic Study of Asteroid Families from KMTNet-SAAO Multi-band Photometry）</news:title>
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   <news:title>グラフに対するアンサンブルクラスタリングの比較と応用（ENSEMBLE CLUSTERING FOR GRAPHS: COMPARISONS AND APPLICATIONS）</news:title>
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   <news:title>進化的手法によるデータ駆動の偏微分方程式発見（Data-driven PDE discovery with evolutionary approach）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:genres>Blog</news:genres>
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   <news:genres>Blog</news:genres>
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   <news:title>Deep Eikonal Solvers（Deep Eikonal Solvers）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>不正確なランダム反復法の収束解析（Convergence Analysis of Inexact Randomized Iterative Methods）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>マトリックス化チャネル注意ネットワークによる効率的な単一画像超解像（A Matrix-in-matrix Neural Network for Image Super Resolution）</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>真の近接方策最適化（Truly Proximal Policy Optimization）</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>スマホ運転データで性別を推定する新しい分類器（A Choquet Fuzzy Integral Vertical Bagging Classifier for Mobile Telematics Data Analysis）</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>定常速度モデルが歩行者予測にもたらす示唆（What the Constant Velocity Model Can Teach Us About Pedestrian Motion Prediction）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-19T19:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層視覚注意モデルによる映像圧縮の改善（Improving Video Compression With Deep Visual-Attention Models）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-19T19:12:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>3Dパースを用いた車両認識の革新（Geometry-constrained Car Recognition Using a 3D Perspective Network）</news:title>
   <news:publication_date>2026-08-19T19:12:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/725019</loc>
  <lastmod>2026-08-19T19:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>教師なしネットワーク表現学習の比較研究 (A Comparative Study for Unsupervised Network Representation Learning)</news:title>
   <news:publication_date>2026-08-19T19:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-19T19:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層信念ネットワークによる特徴抽出とLSTMを用いたDDoS検知手法 (DDoS attack detection method based on feature extraction of deep belief network)</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>敵対的バンディットに関する一階境界・分散・ギャップ依存境界 (On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits)</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>臨床試験のコホート選択に対するハイブリッド手法（Hybrid Approaches for Cohort Selection for Clinical Trials）</news:title>
   <news:publication_date>2026-08-19T19:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-19T18:19:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト平均推定の計算困難性（How Hard is Robust Mean Estimation?）</news:title>
   <news:publication_date>2026-08-19T18:19:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725009</loc>
  <lastmod>2026-08-19T18:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント駆動型ビジョンによる姿勢不変物体認識（Pose-invariant object recognition for event-based vision with slow-ELM）</news:title>
   <news:publication_date>2026-08-19T18:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725007</loc>
  <lastmod>2026-08-19T18:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン横断知識転移による教師なし車両再識別（CROSS DOMAIN KNOWLEDGE TRANSFER FOR UNSUPERVISED VEHICLE RE-IDENTIFICATION）</news:title>
   <news:publication_date>2026-08-19T18:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725005</loc>
  <lastmod>2026-08-19T18:17:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デモ不要で模倣学習を実現する方法（Hindsight Generative Adversarial Imitation Learning）</news:title>
   <news:publication_date>2026-08-19T18:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725003</loc>
  <lastmod>2026-08-19T18:17:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス増分学習とDeep Model Consolidation（Class-incremental Learning via Deep Model Consolidation）</news:title>
   <news:publication_date>2026-08-19T18:17:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725001</loc>
  <lastmod>2026-08-19T18:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化ニューラル埋め込みによるテキスト対応協調フィルタリング（Personalized Neural Embeddings for Collaborative Filtering with Text）</news:title>
   <news:publication_date>2026-08-19T18:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724999</loc>
  <lastmod>2026-08-19T18:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ベルヌーイ自己回帰過程と長期依存性（High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence）</news:title>
   <news:publication_date>2026-08-19T18:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724997</loc>
  <lastmod>2026-08-19T17:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市型倉庫における動的商品選択の最適化（Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses）</news:title>
   <news:publication_date>2026-08-19T17:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724995</loc>
  <lastmod>2026-08-19T17:14:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的物体検出チャレンジが示すロボット視覚の次の一手（Probabilistic Object Detection）</news:title>
   <news:publication_date>2026-08-19T17:14:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724993</loc>
  <lastmod>2026-08-19T17:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KL-UCB+方策の理論的根拠と実務的示唆（A Note on KL-UCB+ Policy for the Stochastic Bandit）</news:title>
   <news:publication_date>2026-08-19T17:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724991</loc>
  <lastmod>2026-08-19T17:13:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全なチャネル知識下での効率的なMIMO検出（Efficient MIMO Detection with Imperfect Channel Knowledge – A Deep Learning Approach）</news:title>
   <news:publication_date>2026-08-19T17:13:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724989</loc>
  <lastmod>2026-08-19T17:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負表現に基づく識別的辞書学習による顔認識（Non-negative representation based discriminative dictionary learning for face recognition）</news:title>
   <news:publication_date>2026-08-19T17:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724987</loc>
  <lastmod>2026-08-19T17:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク識別的最小二乗回帰による画像分類の改良（Low-Rank Discriminative Least Squares Regression for Image Classification）</news:title>
   <news:publication_date>2026-08-19T17:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724985</loc>
  <lastmod>2026-08-19T17:12:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fisher判別付き最小二乗回帰による画像分類の改良（Fisher Discriminative Least Squares Regression for Image Classification）</news:title>
   <news:publication_date>2026-08-19T17:12:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724983</loc>
  <lastmod>2026-08-19T16:21:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Compressed Sensingを臨床へつなぐデータ駆動学習の実装と示唆（Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning）</news:title>
   <news:publication_date>2026-08-19T16:21:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724981</loc>
  <lastmod>2026-08-19T16:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGアーティファクト除去のための機械学習：ベンチマークの確立（Machine Learning for removing EEG artifacts: Setting the benchmark）</news:title>
   <news:publication_date>2026-08-19T16:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724979</loc>
  <lastmod>2026-08-19T16:20:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性を重視する対話型推薦の設計（Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation）</news:title>
   <news:publication_date>2026-08-19T16:20:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724977</loc>
  <lastmod>2026-08-19T16:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスク指導型スタイル転送ネットワークによる実画像の浄化（Mask-Guided Style Transfer Network for Purifying Real Images）</news:title>
   <news:publication_date>2026-08-19T16:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724975</loc>
  <lastmod>2026-08-19T16:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主題に寄り添う文字表現の自動生成（Trick or Treat: Thematic Reinforcement for Artistic Typography）</news:title>
   <news:publication_date>2026-08-19T16:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724973</loc>
  <lastmod>2026-08-19T16:19:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嗅覚の快不快をCNNで予測する試み（POP-CNN: Predicting Odor’s Pleasantness）</news:title>
   <news:publication_date>2026-08-19T16:19:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724971</loc>
  <lastmod>2026-08-19T16:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり深層学習による異常脳波検出の実用性（A semi-supervised deep learning algorithm for abnormal EEG identification）</news:title>
   <news:publication_date>2026-08-19T16:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724969</loc>
  <lastmod>2026-08-19T15:26:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己重み付けマルチビュー距離学習による相互相関最大化（SELF-WEIGHTED MULTIVIEW METRIC LEARNING BY MAXIMIZING THE CROSS CORRELATIONS）</news:title>
   <news:publication_date>2026-08-19T15:26:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724967</loc>
  <lastmod>2026-08-19T15:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>酸素殻燃焼の多次元シミュレーション――超新星直前の対流の実像（One-, Two-, and Three-dimensional Simulations of Oxygen Shell Burning Just Before the Core-Collapse of Massive Stars）</news:title>
   <news:publication_date>2026-08-19T15:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724965</loc>
  <lastmod>2026-08-19T15:26:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ハースト指数（Dynamic Hurst Exponent in Time Series）</news:title>
   <news:publication_date>2026-08-19T15:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724963</loc>
  <lastmod>2026-08-19T15:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライベート合意に基づく分散最適化（Differentially Private Consensus-Based Distributed Optimization）</news:title>
   <news:publication_date>2026-08-19T15:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724961</loc>
  <lastmod>2026-08-19T15:25:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管分割のための動的深層ネットワーク（Dynamic Deep Networks for Retinal Vessel Segmentation）</news:title>
   <news:publication_date>2026-08-19T15:25:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724959</loc>
  <lastmod>2026-08-19T15:25:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆密度推定におけるウェーブレット変換と機械学習の応用（Estimation of crowd density applying wavelet transform and machine learning）</news:title>
   <news:publication_date>2026-08-19T15:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724957</loc>
  <lastmod>2026-08-19T15:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則領域における都市全域の群衆流予測（Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-19T15:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724955</loc>
  <lastmod>2026-08-19T14:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚刺激のカテゴリ復元にBRNNを適用する研究（Category decoding of visual stimuli from human brain activity using a bidirectional recurrent neural network）</news:title>
   <news:publication_date>2026-08-19T14:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724953</loc>
  <lastmod>2026-08-19T14:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズを内側から直す仕組み：PENCIL（Probabilistic End-to-end Noise Correction for Learning with Noisy Labels）</news:title>
   <news:publication_date>2026-08-19T14:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724951</loc>
  <lastmod>2026-08-19T14:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドソーシングと機械学習の協働が変えるデータラベリングの現場（Modeling with the Crowd: Optimizing the Human-Machine Partnership with Zooniverse）</news:title>
   <news:publication_date>2026-08-19T14:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724949</loc>
  <lastmod>2026-08-19T14:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコリレーションによる深層強化学習の表現学習改善（Deep Reinforcement Learning with Decorrelation）</news:title>
   <news:publication_date>2026-08-19T14:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724947</loc>
  <lastmod>2026-08-19T14:32:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子加速器の最適化を飛躍的に高速化する機械学習手法（Machine Learning for Orders of Magnitude Speedup in Multi-Objective Optimization of Particle Accelerator Systems）</news:title>
   <news:publication_date>2026-08-19T14:32:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724945</loc>
  <lastmod>2026-08-19T14:32:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情可視化ジャーナルLemotif（Lemotif: An Affective Visual Journal Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-19T14:32:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724943</loc>
  <lastmod>2026-08-19T14:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ルーティング混合専門家モデルの要点解説（Hierarchical Routing Mixture of Experts）</news:title>
   <news:publication_date>2026-08-19T14:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724941</loc>
  <lastmod>2026-08-19T13:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河分類の機械学習解析（Galaxy classification: A machine learning analysis of GAMA catalogue data）</news:title>
   <news:publication_date>2026-08-19T13:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724939</loc>
  <lastmod>2026-08-19T13:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変動を柔軟に扱う対比較モデル（Pairwise Comparisons with Flexible Time-Dynamics）</news:title>
   <news:publication_date>2026-08-19T13:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724937</loc>
  <lastmod>2026-08-19T13:39:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合で学ぶ複数インスタンス回帰—リモートセンシングへの応用（Learning with Sets in Multiple Instance Regression Applied to Remote Sensing）</news:title>
   <news:publication_date>2026-08-19T13:39:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724935</loc>
  <lastmod>2026-08-19T13:38:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>劣化ブロードキャストチャネルにおける深層学習（Deep Learning for the Degraded Broadcast Channel）</news:title>
   <news:publication_date>2026-08-19T13:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724933</loc>
  <lastmod>2026-08-19T13:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌跡分類のための異種部分列発見（Discovering Heterogeneous Subsequences for Trajectory Classification）</news:title>
   <news:publication_date>2026-08-19T13:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724931</loc>
  <lastmod>2026-08-19T13:38:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的な「人」の到達可能領域を予測する手法（Predicting Stochastic Human Forward Reachable Sets Based on Learned Human Behavior）</news:title>
   <news:publication_date>2026-08-19T13:38:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724929</loc>
  <lastmod>2026-08-19T13:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成深度画像の拡張学習によるシム2リアル方策転移（Learning to Augment Synthetic Images for Sim2Real Policy Transfer）</news:title>
   <news:publication_date>2026-08-19T13:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724927</loc>
  <lastmod>2026-08-19T12:46:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視線の届かない場所での物体認識（Direct Object Recognition Without Line-of-Sight Using Optical Coherence）</news:title>
   <news:publication_date>2026-08-19T12:46:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724925</loc>
  <lastmod>2026-08-19T12:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的な隠れ音声攻撃が示す脅威と備え（Practical Hidden Voice Attacks against Speech and Speaker Recognition Systems）</news:title>
   <news:publication_date>2026-08-19T12:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724923</loc>
  <lastmod>2026-08-19T12:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Real and Discreteを用いた深層混合モデルの新展開（A RAD approach to deep mixture models）</news:title>
   <news:publication_date>2026-08-19T12:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724921</loc>
  <lastmod>2026-08-19T12:45:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的な閉じ込めが引き起こす超臨界流体の構造と動力学（Soft-wall induced structure and dynamics of partially confined supercritical fluids）</news:title>
   <news:publication_date>2026-08-19T12:45:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724919</loc>
  <lastmod>2026-08-19T12:45:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アプリケーション駆動のDNNアクセラレータ設計空間探索（Software-Defined Design Space Exploration for an Efficient DNN Accelerator Architecture）</news:title>
   <news:publication_date>2026-08-19T12:45:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724917</loc>
  <lastmod>2026-08-19T12:44:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ファンダメンタル因子モデルの実務的意義（Deep Fundamental Factor Models）</news:title>
   <news:publication_date>2026-08-19T12:44:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724915</loc>
  <lastmod>2026-08-19T12:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Duet v2によるパッセージ再ランキングの改良（AN UPDATED DUET MODEL FOR PASSAGE RE-RANKING）</news:title>
   <news:publication_date>2026-08-19T12:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724913</loc>
  <lastmod>2026-08-19T11:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IllustrisTNGと深層学習で読み解く銀河形態の再現性（The Hubble Sequence at z ∼0 in the IllustrisTNG simulation with deep learning）</news:title>
   <news:publication_date>2026-08-19T11:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724911</loc>
  <lastmod>2026-08-19T11:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOODS領域における微弱電波源の本質（Nature of Faint Radio Sources in GOODS-North and GOODS-South Fields – I. Spectral Index and Radio-FIR Correlation）</news:title>
   <news:publication_date>2026-08-19T11:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724909</loc>
  <lastmod>2026-08-19T11:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス分類器の多重差分公平性監査（Multi-Differential Fairness Auditor for Black Box Classifiers）</news:title>
   <news:publication_date>2026-08-19T11:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724907</loc>
  <lastmod>2026-08-19T11:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字レベルCNNによるテキスト分類とエンコーディングの比較（Character-level Convolutional Networks for Text Classification）</news:title>
   <news:publication_date>2026-08-19T11:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724905</loc>
  <lastmod>2026-08-19T11:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間の循環一貫性から学ぶ対応関係（Learning Correspondence from the Cycle-consistency of Time）</news:title>
   <news:publication_date>2026-08-19T11:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724903</loc>
  <lastmod>2026-08-19T11:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル不確実性とパラメータ不確実性を同時に扱うベイズニューラルネットワーク（Combining model and parameter uncertainty in Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-19T11:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724901</loc>
  <lastmod>2026-08-19T11:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフ畳み込みネットワークによる推薦システム（Knowledge Graph Convolutional Networks for Recommender Systems）</news:title>
   <news:publication_date>2026-08-19T11:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724899</loc>
  <lastmod>2026-08-19T10:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い特徴量に関する二重降下モデル（Two models of double descent for weak features）</news:title>
   <news:publication_date>2026-08-19T10:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724897</loc>
  <lastmod>2026-08-19T10:58:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボコーダーを用いた歌声抽出法（A VOCODER BASED METHOD FOR SINGING VOICE EXTRACTION）</news:title>
   <news:publication_date>2026-08-19T10:58:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724895</loc>
  <lastmod>2026-08-19T10:58:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>失敗の動態を定量化する（Quantifying dynamics of failure across science, startups, and security）</news:title>
   <news:publication_date>2026-08-19T10:58:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724893</loc>
  <lastmod>2026-08-19T10:57:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EV-IMO: 屋内高速物体のイベントカメラによる動き分割とデータセット（EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras）</news:title>
   <news:publication_date>2026-08-19T10:57:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724891</loc>
  <lastmod>2026-08-19T10:57:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動ガンマ過程下でのアメリカン・オプション高速評価法（A fast method for pricing American options under the variance gamma model）</news:title>
   <news:publication_date>2026-08-19T10:57:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724889</loc>
  <lastmod>2026-08-19T10:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Short Datathonによるデータ分析・可視化スキル育成（Short Datathon for the Interdisciplinary Development of Data Analysis and Visualization Skills）</news:title>
   <news:publication_date>2026-08-19T10:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724887</loc>
  <lastmod>2026-08-19T10:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の注目を活かす画像キャプション生成の強化（Boosted Attention: Leveraging Human Attention for Image Captioning）</news:title>
   <news:publication_date>2026-08-19T10:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724885</loc>
  <lastmod>2026-08-19T10:06:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークによる経路の外挿（Extrapolating paths with graph neural networks）</news:title>
   <news:publication_date>2026-08-19T10:06:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724883</loc>
  <lastmod>2026-08-19T10:06:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指数族モデルを丸ごと学習する二つのネットワーク構成（Approximating exponential family models with a two-network architecture）</news:title>
   <news:publication_date>2026-08-19T10:06:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724881</loc>
  <lastmod>2026-08-19T10:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期気象予測の予測手法比較（A Comparison of Prediction Algorithms and Nexting for Short Term Weather Forecasts）</news:title>
   <news:publication_date>2026-08-19T10:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724879</loc>
  <lastmod>2026-08-19T10:04:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語による画像編集のビリニア表現（BILINEAR REPRESENTATION FOR LANGUAGE-BASED IMAGE EDITING USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-08-19T10:04:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724877</loc>
  <lastmod>2026-08-19T10:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNベースの絶対カメラ姿勢回帰の限界（Understanding the Limitations of CNN-based Absolute Camera Pose Regression）</news:title>
   <news:publication_date>2026-08-19T10:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724875</loc>
  <lastmod>2026-08-19T10:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効果的なラベルノイズモデルによるDNNテキスト分類の頑強化（An Effective Label Noise Model for DNN Text Classification）</news:title>
   <news:publication_date>2026-08-19T10:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724873</loc>
  <lastmod>2026-08-19T10:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークと新規前処理でアルツハイマー病の進行を予測する（Forecasting the Progression of Alzheimer’s Disease Using Neural Networks and a Novel Pre-Processing Algorithm）</news:title>
   <news:publication_date>2026-08-19T10:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724871</loc>
  <lastmod>2026-08-19T09:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認知による高度なカプセルネットワーク（Advanced Capsule Networks via Context Awareness）</news:title>
   <news:publication_date>2026-08-19T09:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724869</loc>
  <lastmod>2026-08-19T09:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-19T09:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724867</loc>
  <lastmod>2026-08-19T09:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフラインとオンラインの深層学習による画像認識（Offline and Online Deep Learning for Image Recognition）</news:title>
   <news:publication_date>2026-08-19T09:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724865</loc>
  <lastmod>2026-08-19T09:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MUSEFood：スマートフォンでのマルチセンサによる食品容積推定（MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones）</news:title>
   <news:publication_date>2026-08-19T09:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724863</loc>
  <lastmod>2026-08-19T09:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層構造を利用したKL正則化強化学習の学習と転移（Exploiting Hierarchy for Learning and Transfer in KL-regularized RL）</news:title>
   <news:publication_date>2026-08-19T09:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724861</loc>
  <lastmod>2026-08-19T09:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信効率を劇的に改善する連合学習の仕組み（Communication-Efficient Federated Deep Learning with Asynchronous Model Update and Temporally Weighted Aggregation）</news:title>
   <news:publication_date>2026-08-19T09:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724859</loc>
  <lastmod>2026-08-19T09:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>n部分トーナメントの部分自己同型写像の拡張（EXTENDING PARTIAL AUTOMORPHISMS OF n-PARTITE TOURNAMENTS）</news:title>
   <news:publication_date>2026-08-19T09:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724857</loc>
  <lastmod>2026-08-19T08:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最近傍量子化フィルタに基づく分位点回帰による確率的エネルギー予測（Probabilistic Energy Forecasting using Quantile Regressions based on a new Nearest Neighbors Quantile Filter）</news:title>
   <news:publication_date>2026-08-19T08:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724855</loc>
  <lastmod>2026-08-19T08:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索駆動を階層化する新戦略：Scheduled Intrinsic Drive（Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration）</news:title>
   <news:publication_date>2026-08-19T08:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724853</loc>
  <lastmod>2026-08-19T08:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア工学が社会心理学の感情研究から学べること（What software engineering can learn from research on affect in social psychology）</news:title>
   <news:publication_date>2026-08-19T08:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724851</loc>
  <lastmod>2026-08-19T08:17:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUニューラルネットワークのオンライントレーニング挙動の解析（On-line learning dynamics of ReLU neural networks using statistical physics techniques）</news:title>
   <news:publication_date>2026-08-19T08:17:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724849</loc>
  <lastmod>2026-08-19T08:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CRAFTによる音声プロソディ可視化の教育的転換（CRAFT: A Multifunction Online Platform for Speech Prosody Visualisation）</news:title>
   <news:publication_date>2026-08-19T08:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724847</loc>
  <lastmod>2026-08-19T08:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き文字認識のためのシーケンス・トゥ・シーケンスモデル評価（Evaluating Sequence-to-Sequence Models for Handwritten Text Recognition）</news:title>
   <news:publication_date>2026-08-19T08:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724845</loc>
  <lastmod>2026-08-19T08:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートメーターで捉える認知症患者の生活行動（Detecting Activities of Daily Living and Routine Behaviours in Dementia Patients Living Alone Using Smart Meter Load Disaggregation）</news:title>
   <news:publication_date>2026-08-19T08:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724843</loc>
  <lastmod>2026-08-19T07:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Eコマース向けファッションアウトフィット生成（Fashion Outfit Generation for E-commerce）</news:title>
   <news:publication_date>2026-08-19T07:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724841</loc>
  <lastmod>2026-08-19T07:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチンゲール表現によるマルコフ連鎖の分散削減（Variance reduction for additive functional of Markov chains via martingale representations）</news:title>
   <news:publication_date>2026-08-19T07:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724839</loc>
  <lastmod>2026-08-19T07:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知光源下での自己校正フォトメトリーステレオ（Self-calibrating Deep Photometric Stereo Networks）</news:title>
   <news:publication_date>2026-08-19T07:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724837</loc>
  <lastmod>2026-08-19T07:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>印刷可能なグラフィカルコードの複製可能性と機械学習による解析（CLONABILITY OF ANTI-COUNTERFEITING PRINTABLE GRAPHICAL CODES: A MACHINE LEARNING APPROACH）</news:title>
   <news:publication_date>2026-08-19T07:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724835</loc>
  <lastmod>2026-08-19T07:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数値モデルの不明部分の機械学習による表現（Representing ill-known parts of a numerical model using a machine learning approach）</news:title>
   <news:publication_date>2026-08-19T07:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724833</loc>
  <lastmod>2026-08-19T07:13:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IvaNetによる物体検出とセグメンテーションの同時学習（IVANET: LEARNING TO JOINTLY DETECT AND SEGMENT OBJETS WITH THE HELP OF LOCAL TOP-DOWN MODULES）</news:title>
   <news:publication_date>2026-08-19T07:13:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724831</loc>
  <lastmod>2026-08-19T07:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Xホールを用いたF-RANのオンライン強化学習によるコンテンツ配信最適化（Online Reinforcement Learning of X-Haul Content Delivery Mode in Fog Radio Access Networks）</news:title>
   <news:publication_date>2026-08-19T07:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724829</loc>
  <lastmod>2026-08-19T06:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合データ学習と集約関数の選び方（On Deep Set Learning and the Choice of Aggregations）</news:title>
   <news:publication_date>2026-08-19T06:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724827</loc>
  <lastmod>2026-08-19T06:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IMDBとTwitterデータに対する感情分析 — 機械学習とベクトル空間による手法 (Sentiment Analysis on IMDB Movie Comments and Twitter Data by Machine Learning and Vector Space Techniques)</news:title>
   <news:publication_date>2026-08-19T06:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724825</loc>
  <lastmod>2026-08-19T06:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多系列MRIを用いた深層学習による脳転移の自動検出とセグメンテーション（Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI）</news:title>
   <news:publication_date>2026-08-19T06:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724823</loc>
  <lastmod>2026-08-19T06:21:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左右循環制約と適応正則化による教師なし単眼深度推定（Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction）</news:title>
   <news:publication_date>2026-08-19T06:21:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724821</loc>
  <lastmod>2026-08-19T06:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRIベースのアルツハイマー病分類におけるLRPによる説明性の向上（Layer-wise relevance propagation for explaining deep neural network decisions in MRI-based Alzheimer’s disease classification）</news:title>
   <news:publication_date>2026-08-19T06:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724819</loc>
  <lastmod>2026-08-19T06:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Gaussian Processesを用いたマルチフィデリティモデリング（Deep Gaussian Processes for Multi-fidelity Modeling）</news:title>
   <news:publication_date>2026-08-19T06:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724817</loc>
  <lastmod>2026-08-19T06:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク近似による双曲線埋め込みの効率化（Low-rank approximations of hyperbolic embeddings）</news:title>
   <news:publication_date>2026-08-19T06:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724815</loc>
  <lastmod>2026-08-19T05:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M²VAEによるマルチモーダル生成の論点整理（M²VAE – Derivation of a Multi-Modal Variational Autoencoder）</news:title>
   <news:publication_date>2026-08-19T05:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724813</loc>
  <lastmod>2026-08-19T05:28:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ系列の自己回帰モデル（Autoregressive Models for Sequences of Graphs）</news:title>
   <news:publication_date>2026-08-19T05:28:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724811</loc>
  <lastmod>2026-08-19T05:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチユーザ分散型大規模MIMOのパイロット設計に深層学習を用いる手法（Deep Learning Based Pilot Design for Multi-user Distributed Massive MIMO Systems）</news:title>
   <news:publication_date>2026-08-19T05:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724809</loc>
  <lastmod>2026-08-19T05:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間適応正規化によるセマンティック画像合成（Semantic Image Synthesis with Spatially-Adaptive Normalization）</news:title>
   <news:publication_date>2026-08-19T05:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724807</loc>
  <lastmod>2026-08-19T05:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観ベースの視線推定における拡張畳み込みの活用（Appearance-Based Gaze Estimation Using Dilated-Convolutions）</news:title>
   <news:publication_date>2026-08-19T05:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724805</loc>
  <lastmod>2026-08-19T05:27:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種グラフに注目する表現学習の新潮流（Heterogeneous Graph Attention Network）</news:title>
   <news:publication_date>2026-08-19T05:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724803</loc>
  <lastmod>2026-08-19T05:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パディングがLSTMとCNNの振る舞いに与える影響（Effects of Padding on LSTMs and CNNs）</news:title>
   <news:publication_date>2026-08-19T05:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724801</loc>
  <lastmod>2026-08-19T04:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き生成敵対ネットワークによる敵対的事例生成（Generating Adversarial Examples With Conditional Generative Adversarial Net）</news:title>
   <news:publication_date>2026-08-19T04:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724799</loc>
  <lastmod>2026-08-19T04:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 1052周辺で見つかった複数の恒星ストリームの検出（A tidal tale: detection of multiple stellar streams in the environment of NGC 1052）</news:title>
   <news:publication_date>2026-08-19T04:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724797</loc>
  <lastmod>2026-08-19T04:35:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込み構造を用いたPOI意味モデル（POI Semantic Model with a Deep Convolutional Structure）</news:title>
   <news:publication_date>2026-08-19T04:35:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724795</loc>
  <lastmod>2026-08-19T04:35:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-19T04:35:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期待認識型プランニングの統一的枠組み（Expectation-Aware Planning）</news:title>
   <news:publication_date>2026-08-19T04:35:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724791</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>EEGによる感情認識と機械学習の実装と評価（Emotion Recognition with Machine Learning Using EEG Signals）</news:title>
   <news:publication_date>2026-08-19T04:35:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724789</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>概念ドリフト下のプロトタイプ分類器の挙動解析（Prototype-based classifiers in the presence of concept drift: A modelling framework）</news:title>
   <news:publication_date>2026-08-19T04:34:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724787</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>分散最適化におけるアニーリングによる大域解収束（Annealing for Distributed Global Optimization）</news:title>
   <news:publication_date>2026-08-19T03:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724785</loc>
  <lastmod>2026-08-19T03:43:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みによるラベルノイズクリーナ（Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection）</news:title>
   <news:publication_date>2026-08-19T03:43:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-19T03:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質認識テンプレートマッチング（Quality-Aware Template Matching For Deep Learning）</news:title>
   <news:publication_date>2026-08-19T03:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724781</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>準確率的近似の収束速度最適性（Optimal Rate of Convergence for Quasi-Stochastic Approximation）</news:title>
   <news:publication_date>2026-08-19T03:42:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724779</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>複雑なPolSAR画像のシーン分類に向けた自己段階学習（Complex Scene Classification of PolSAR Imagery Based on a Self-Paced Learning Approach）</news:title>
   <news:publication_date>2026-08-19T03:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-19T03:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みによる対位法（Counterpoint by Convolution）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可搬型加速度計と深層学習で現場の地面反力を推定する（Multidimensional ground reaction forces and moments from wearable sensor accelerations via deep learning）</news:title>
   <news:publication_date>2026-08-19T02:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>射影を用いた状態安定性から見るエピソディック学習の制御理論的解析（A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability）</news:title>
   <news:publication_date>2026-08-19T02:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-19T02:49:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの衣服アニメーションによるバーチャルトライオン（Learning-Based Animation of Clothing for Virtual Try-On）</news:title>
   <news:publication_date>2026-08-19T02:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-19T02:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模かつ密な部分相関ネットワークの計算と応用（On the Computation and Applications of Large Dense Partial Correlation Networks）</news:title>
   <news:publication_date>2026-08-19T02:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-19T02:49:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AttoNetsによるエッジ向け超小型高効率ニューラルネットワーク（AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design）</news:title>
   <news:publication_date>2026-08-19T02:49:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル・フリーによるモデル調整（Model-Free Model Reconciliation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の“精度”は操作できる—がん予測研究の暗部（Machine Learning: A Dark Side of Cancer Computing）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文認識を変えるポインタネットワーク応用（Syntax-aware Representation Learning With Pointer Networks）</news:title>
   <news:publication_date>2026-08-19T01:57:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724755</loc>
  <lastmod>2026-08-19T01:57:01Z</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>2026-08-19T01:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間と機械の相互作用を最小限の仮定で設計する（Modeling and Optimization of Human-Machine Interaction Processes via the Maximum Entropy Principle）</news:title>
   <news:publication_date>2026-08-19T01:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JWSTによるトランジット系外惑星の分光特性化（Characterizing Transiting Exoplanets with JWST）</news:title>
   <news:publication_date>2026-08-19T01:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724749</loc>
  <lastmod>2026-08-19T01:56:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳に学ぶ高スパースニューラルネットワークの訓練アルゴリズム（A Brain-inspired Algorithm for Training Highly Sparse Neural Networks）</news:title>
   <news:publication_date>2026-08-19T01:56:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724747</loc>
  <lastmod>2026-08-19T01:55:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像復元のための近接分割ネットワーク（Proximal Splitting Networks for Image Restoration）</news:title>
   <news:publication_date>2026-08-19T01:55:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724745</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>深いResNetの安定化と鋭いスケーリング係数τ (Stabilize Deep ResNet with A Sharp Scaling Factor τ)</news:title>
   <news:publication_date>2026-08-19T01:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724743</loc>
  <lastmod>2026-08-19T01:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック誘導型変分オートエンコーダによる文章生成（Topic-Guided Variational Autoencoders for Text Generation）</news:title>
   <news:publication_date>2026-08-19T01:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724741</loc>
  <lastmod>2026-08-19T01:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブ抽出テーブルとパイプラインモデルによる質問応答 (Question Answering via Web Extracted Tables and Pipelined Models)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-19T01:02:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分人物再識別のための対ペア空間変換ネットワーク（STNReID: Deep Convolutional Networks with Pairwise Spatial Transformer Networks for Partial Person Re-identification）</news:title>
   <news:publication_date>2026-08-19T01:02:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データベースで予測を直接実行する仕組み（tspDB: Time Series Predict DB）</news:title>
   <news:publication_date>2026-08-19T01:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-19T01:02:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>用量探索試験におけるマルチアームド・バンディット設計の応用（On Multi-Armed Bandit Designs for Dose-Finding Trials）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-19T01:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師-生徒ネットワークを用いた深層特徴選択（Deep Feature Selection using a Teacher-Student Network）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdaGraphによる予測的・連続的ドメイン適応の統一（AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-19T00:03:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層人物再識別の強力なベースラインとトレーニングの小技集 (Bag of Tricks and A Strong Baseline for Deep Person Re-identification)</news:title>
   <news:publication_date>2026-08-19T00:03:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントベース映像に対する時空間フィルタの応用（Spatiotemporal Filtering for Event-Based Action Recognition）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T23:08:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T23:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T22:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T22:16:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T22:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>無秩序から秩序を学ぶ（Learning to find order in disorder）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分割（パーティション）中心の分散アルゴリズムによる大規模グラフのオイラー回路探索（A Partition-centric Distributed Algorithm for Identifying Euler Circuits in Large Graphs）</news:title>
   <news:publication_date>2026-08-18T21:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T21:22:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T20:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
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    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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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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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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  <lastmod>2026-08-18T14:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な太陽電池材料の高速探索（Accelerated Discovery of Efficient Solar-cell Materials using Quantum and Machine-learning Methods）</news:title>
   <news:publication_date>2026-08-18T14:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724577</loc>
  <lastmod>2026-08-18T14:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異方的な堅牢性の証明：非一様境界の検証（On Certifying Non-uniform Bounds against Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-18T14:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724575</loc>
  <lastmod>2026-08-18T14:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的畳み込みニューラルネットワークによる動画物体検出の高速化（SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection）</news:title>
   <news:publication_date>2026-08-18T14:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724573</loc>
  <lastmod>2026-08-18T14:02:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列分類における深層ニューラルネットワークのアンサンブル（Deep Neural Network Ensembles for Time Series Classification）</news:title>
   <news:publication_date>2026-08-18T14:02:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724571</loc>
  <lastmod>2026-08-18T14:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策蒸留と価値マッチングによるマルチエージェント強化学習の統合（Policy Distillation and Value Matching in Multiagent Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T14:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724569</loc>
  <lastmod>2026-08-18T14:01:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モンテカルロ・ウェーブレットによるフレーム離散化（Monte Carlo wavelets: a randomized approach to frame discretization）</news:title>
   <news:publication_date>2026-08-18T14:01:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724567</loc>
  <lastmod>2026-08-18T14:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的M推定量の任意時点非漸近反復対数則（A nonasymptotic law of iterated logarithm for general M-estimators）</news:title>
   <news:publication_date>2026-08-18T14:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724565</loc>
  <lastmod>2026-08-18T14:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的カーネルネットワーク（Selective Kernel Networks）</news:title>
   <news:publication_date>2026-08-18T14:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724563</loc>
  <lastmod>2026-08-18T13:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画への動画挿入手法（Inserting Videos into Videos）</news:title>
   <news:publication_date>2026-08-18T13:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724561</loc>
  <lastmod>2026-08-18T13:09:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有状態の局所測定から系のハミルトニアンを復元する（Determining system Hamiltonian from eigenstate measurements without correlation functions）</news:title>
   <news:publication_date>2026-08-18T13:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724559</loc>
  <lastmod>2026-08-18T13:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ラベルによる雲画像分割（Multi-label Cloud Segmentation Using a Deep Network）</news:title>
   <news:publication_date>2026-08-18T13:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724557</loc>
  <lastmod>2026-08-18T13:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゴルフスイングの「映像イベント検出」が変える分析実務（GolfDB: A Video Database for Golf Swing Sequencing）</news:title>
   <news:publication_date>2026-08-18T13:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724555</loc>
  <lastmod>2026-08-18T13:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スループットイメージング解析における表現型プロファイリング（Phenotypic Profiling of High Throughput Imaging Screens with Generic Deep Convolutional Features）</news:title>
   <news:publication_date>2026-08-18T13:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724553</loc>
  <lastmod>2026-08-18T13:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テニスランキングの新モデル：非負行列因子分解に動機づけられたランキングモデル（A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments）</news:title>
   <news:publication_date>2026-08-18T13:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724551</loc>
  <lastmod>2026-08-18T13:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃的発言検出の最先端手法の探索（An Exploration of State-of-the-art Methods for Offensive Language Detection）</news:title>
   <news:publication_date>2026-08-18T13:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724549</loc>
  <lastmod>2026-08-18T12:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル融合の自動設計探索（MFAS: Multimodal Fusion Architecture Search）</news:title>
   <news:publication_date>2026-08-18T12:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724547</loc>
  <lastmod>2026-08-18T12:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロモーフィックハードウェアにおける学習の学習（Neuromorphic Hardware learns to learn）</news:title>
   <news:publication_date>2026-08-18T12:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724545</loc>
  <lastmod>2026-08-18T12:15:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重バイオメトリクスによる双子識別（Twins Recognition with Multi Biometric System）</news:title>
   <news:publication_date>2026-08-18T12:15:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724543</loc>
  <lastmod>2026-08-18T12:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈対応型引用推薦モデルが変える参考文献探索（A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-18T12:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724541</loc>
  <lastmod>2026-08-18T12:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミングを用いた感情コンピューティングの実践（Applying Probabilistic Programming to Affective Computing）</news:title>
   <news:publication_date>2026-08-18T12:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724539</loc>
  <lastmod>2026-08-18T12:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの濃密セマンティック再構築（Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations）</news:title>
   <news:publication_date>2026-08-18T12:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724537</loc>
  <lastmod>2026-08-18T12:14:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>国際株式市場を同時に扱うマルチモーダル深層学習（Multimodal Deep Learning for Finance: Integrating and Forecasting International Stock Markets）</news:title>
   <news:publication_date>2026-08-18T12:14:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724535</loc>
  <lastmod>2026-08-18T11:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠における皮質覚醒の自動検出と日中の眠気への寄与（Automatic Detection of Cortical Arousals in Sleep and their Contribution to Daytime Sleepiness）</news:title>
   <news:publication_date>2026-08-18T11:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724533</loc>
  <lastmod>2026-08-18T11:22:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限体上の重要特徴列挙を高速化するアルゴリズム（A Faster Algorithm Enumerating Relevant Features over Finite Fields）</news:title>
   <news:publication_date>2026-08-18T11:22:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724531</loc>
  <lastmod>2026-08-18T11:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>児童の第二言語音声能力を自動評価する技術の実用性（AUTOMATIC ASSESSMENT OF SPOKEN LANGUAGE PROFICIENCY OF NON-NATIVE CHILDREN）</news:title>
   <news:publication_date>2026-08-18T11:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724529</loc>
  <lastmod>2026-08-18T11:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ブラックボックス最適化ベンチマーク（COCO: The Large Scale Black-Box Optimization Benchmarking）</news:title>
   <news:publication_date>2026-08-18T11:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724527</loc>
  <lastmod>2026-08-18T11:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DFineNetによる深度補完と自己位置推定の統合（DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance）</news:title>
   <news:publication_date>2026-08-18T11:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724525</loc>
  <lastmod>2026-08-18T11:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質を意識した非対応画像間翻訳（Quality-aware Unpaired Image-to-Image Translation）</news:title>
   <news:publication_date>2026-08-18T11:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724523</loc>
  <lastmod>2026-08-18T11:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次Dysthe方程式における変調波の数値シミュレーション（Numerical simulations of modulated waves in a higher-order Dysthe equation）</news:title>
   <news:publication_date>2026-08-18T11:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724521</loc>
  <lastmod>2026-08-18T10:26:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載レーダーの干渉除去に向けた深層学習アプローチ（A Deep Learning Approach for Automotive Radar Interference Mitigation）</news:title>
   <news:publication_date>2026-08-18T10:26:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724519</loc>
  <lastmod>2026-08-18T10:26:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイクベースの逆伝播による深層ニューラルネットワーク訓練の実現 (Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures)</news:title>
   <news:publication_date>2026-08-18T10:26:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724517</loc>
  <lastmod>2026-08-18T10:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FASTのドリフトスキャンにおけるパルサー候補選別のための集合ネットワーク（Pulsar Candidate Selection Using Ensemble Networks for FAST Drift-Scan Survey）</news:title>
   <news:publication_date>2026-08-18T10:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724515</loc>
  <lastmod>2026-08-18T10:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散強化学習におけるマルチエージェント・オフポリシー アクタークリティック（A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T10:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724513</loc>
  <lastmod>2026-08-18T10:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量光学フローCNNの再設計（A Lightweight Optical Flow CNN — Revisiting Data Fidelity and Regularization）</news:title>
   <news:publication_date>2026-08-18T10:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724511</loc>
  <lastmod>2026-08-18T10:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数変調による異方性量子ラビモデルのシミュレーション（Simulating Anisotropic quantum Rabi model via frequency modulation）</news:title>
   <news:publication_date>2026-08-18T10:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724509</loc>
  <lastmod>2026-08-18T10:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と物の相互作用認識と姿勢推定のターボ学習フレームワーク（Turbo Learning Framework for Human-Object Interactions Recognition and Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-18T10:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724507</loc>
  <lastmod>2026-08-18T09:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像分類のための教師なし深層転移特徴学習（UNSUPERVISED DEEP TRANSFER FEATURE LEARNING FOR MEDICAL IMAGE CLASSIFICATION）</news:title>
   <news:publication_date>2026-08-18T09:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724505</loc>
  <lastmod>2026-08-18T09:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲットシフトに配慮した敵対的ドメイン適応（On Target Shift in Adversarial Domain Adaptation）</news:title>
   <news:publication_date>2026-08-18T09:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724503</loc>
  <lastmod>2026-08-18T09:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いたリスクモデルの実務的意義（Machine Learning Risk Models）</news:title>
   <news:publication_date>2026-08-18T09:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724501</loc>
  <lastmod>2026-08-18T09:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の逐次改良を可能にするDeep Joint Source-Channel Coding（Successive Refinement of Images with Deep Joint Source-Channel Coding）</news:title>
   <news:publication_date>2026-08-18T09:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724499</loc>
  <lastmod>2026-08-18T09:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトマルチラベル学習による教師なし人物再識別（Unsupervised Person Re-identification by Soft Multilabel Learning）</news:title>
   <news:publication_date>2026-08-18T09:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724497</loc>
  <lastmod>2026-08-18T09:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期セントロイド問題に挑むDP-KMeans（Tackling Initial Centroid of K-Means with Distance Part (DP-KMeans)）</news:title>
   <news:publication_date>2026-08-18T09:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724495</loc>
  <lastmod>2026-08-18T09:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽系の深時間サーベイ（Solar system Deep Time‑Surveys of atmospheres, surfaces, and rings）</news:title>
   <news:publication_date>2026-08-18T09:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724493</loc>
  <lastmod>2026-08-18T08:39:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウィンドウ化された姿勢グラフ最適化による教師なし単眼Visual Odometryの改善（Pose Graph Optimization for Unsupervised Monocular Visual Odometry）</news:title>
   <news:publication_date>2026-08-18T08:39:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724491</loc>
  <lastmod>2026-08-18T08:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互線形回帰に基づく離散ハッシュ（MUTUAL LINEAR REGRESSION-BASED DISCRETE HASHING）</news:title>
   <news:publication_date>2026-08-18T08:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724489</loc>
  <lastmod>2026-08-18T08:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家の視線を模倣する試み（Toward Imitating Visual Attention of Experts in Software Development Tasks）</news:title>
   <news:publication_date>2026-08-18T08:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724487</loc>
  <lastmod>2026-08-18T08:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的モデルによる相関攻撃への防御研究アジェンダ（A Research Agenda: Dynamic Models to Defend Against Correlated Attacks）</news:title>
   <news:publication_date>2026-08-18T08:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724485</loc>
  <lastmod>2026-08-18T08:37:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散制約オンライン学習（Distributed Constrained Online Learning）</news:title>
   <news:publication_date>2026-08-18T08:37:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724483</loc>
  <lastmod>2026-08-18T08:37:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ROS2Learn：ROS 2向け強化学習フレームワーク（ROS2Learn: a reinforcement learning framework for ROS 2）</news:title>
   <news:publication_date>2026-08-18T08:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724481</loc>
  <lastmod>2026-08-18T08:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>gym-gazebo2を使ったROS 2とGazeboによる強化学習ツールキット（gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and Gazebo）</news:title>
   <news:publication_date>2026-08-18T08:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724479</loc>
  <lastmod>2026-08-18T07:46:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と言語を一つに学ぶ統合モデル（Show, Translate and Tell）</news:title>
   <news:publication_date>2026-08-18T07:46:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724477</loc>
  <lastmod>2026-08-18T07:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャマー抑圧のためのモデル駆動深層学習（Model-Driven Deep Learning Method for Jammer Suppression in Massive Connectivity Systems）</news:title>
   <news:publication_date>2026-08-18T07:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724475</loc>
  <lastmod>2026-08-18T07:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DysLexMLによるディスレクシアのスクリーニング（DysLexML: Screening Tool for Dyslexia Using Machine Learning）</news:title>
   <news:publication_date>2026-08-18T07:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724473</loc>
  <lastmod>2026-08-18T07:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチ学習におけるK-FACの非効率性（Inefficiency of K-FAC for Large Batch Size Training）</news:title>
   <news:publication_date>2026-08-18T07:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724471</loc>
  <lastmod>2026-08-18T07:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調キャッシュ配置における学習オートマトン組み込みQ学習（Learning Automata Based Q-learning for Content Placement in Cooperative Caching）</news:title>
   <news:publication_date>2026-08-18T07:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724469</loc>
  <lastmod>2026-08-18T07:44:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Architecture Searchの分類器改良をアンサンブル学習で実現（Improving Neural Architecture Search Image Classifiers via Ensemble Learning）</news:title>
   <news:publication_date>2026-08-18T07:44:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724467</loc>
  <lastmod>2026-08-18T07:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテデータでの機械学習予測を読み解く（Interpretation of machine learning predictions for patient outcomes in electronic health records）</news:title>
   <news:publication_date>2026-08-18T07:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724465</loc>
  <lastmod>2026-08-18T06:52:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト付き強化学習における後悔ゼロ探索（No-regret Exploration in Contextual Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T06:52:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724463</loc>
  <lastmod>2026-08-18T06:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星合体からの高エネルギー放射（High-energy emissions from neutron star mergers）</news:title>
   <news:publication_date>2026-08-18T06:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724461</loc>
  <lastmod>2026-08-18T06:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河進化を大規模構造の文脈で観測する意義（Observing Galaxy Evolution in the Context of Large-Scale Structure）</news:title>
   <news:publication_date>2026-08-18T06:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724459</loc>
  <lastmod>2026-08-18T06:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非極性二ループ重質量ピュアシングレットWilson係数の解析（The unpolarized two-loop massive pure singlet Wilson coefficients for deep-inelastic scattering）</news:title>
   <news:publication_date>2026-08-18T06:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724457</loc>
  <lastmod>2026-08-18T06:51:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微細な差を見抜く注意機構：Trilinear Attention Sampling Networkによる微粒度画像認識（Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition）</news:title>
   <news:publication_date>2026-08-18T06:51:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724455</loc>
  <lastmod>2026-08-18T06:51:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の修正フィードバックに基づく探索を用いた深層強化学習（Deep Reinforcement Learning with Feedback-based Exploration）</news:title>
   <news:publication_date>2026-08-18T06:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724453</loc>
  <lastmod>2026-08-18T06:51:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WFIRSTで実現する超深場観測（An Ultra Deep Field Survey with WFIRST）</news:title>
   <news:publication_date>2026-08-18T06:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724451</loc>
  <lastmod>2026-08-18T05:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネスト化ポリヘドラルモデルによるテンソルコンパイル（Stripe: Tensor Compilation via the Nested Polyhedral Model）</news:title>
   <news:publication_date>2026-08-18T05:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724449</loc>
  <lastmod>2026-08-18T05:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結びついた超伝導フラックス量子ビットにおける非ストクァスティック・ハミルトニアンの実証（Demonstration of nonstoquastic Hamiltonian in coupled superconducting flux qubits）</news:title>
   <news:publication_date>2026-08-18T05:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724447</loc>
  <lastmod>2026-08-18T05:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スイッチ型ネットワークによる離散データ生成（Deep Switch Networks for Generating Discrete Data and Language）</news:title>
   <news:publication_date>2026-08-18T05:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724445</loc>
  <lastmod>2026-08-18T05:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質独立のJPEG復元のための深い残差オートエンコーダ（Deep Residual Autoencoder for quality independent JPEG restoration）</news:title>
   <news:publication_date>2026-08-18T05:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724443</loc>
  <lastmod>2026-08-18T05:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散化されたAttend-Infer-Repeatによる教師なしで解釈可能なシーン発見（Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat）</news:title>
   <news:publication_date>2026-08-18T05:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724441</loc>
  <lastmod>2026-08-18T05:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀行顧客の潜在表現学習（Learning Latent Representations of Bank Customers With The Variational Autoencoder）</news:title>
   <news:publication_date>2026-08-18T05:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724439</loc>
  <lastmod>2026-08-18T05:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルで圧縮し可視化するニューラルネット（Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer）</news:title>
   <news:publication_date>2026-08-18T05:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724437</loc>
  <lastmod>2026-08-18T05:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MSG-GANによるGANの安定化—マルチスケール勾配で高解像度生成を安定化する（MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-18T05:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724435</loc>
  <lastmod>2026-08-18T04:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-18T04:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-18T04:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-18T04:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724419</loc>
  <lastmod>2026-08-18T04:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療IoTの通信を優先するための機械学習と資源割当の統合設計（Using Machine Learning and Big Data Analytics to Prioritize Outpatients in HetNets）</news:title>
   <news:publication_date>2026-08-18T04:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-18T04:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインGaussian Process状態空間モデル：部分観測ダイナミクスの学習と計画（Online Gaussian Process State-Space Model: Learning and Planning for Partially Observable Dynamical Systems）</news:title>
   <news:publication_date>2026-08-18T04:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-18T04:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゴーストイメージングから学ぶイメージ不要の学習（On Learning from Ghost Imaging without Imaging）</news:title>
   <news:publication_date>2026-08-18T04:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724413</loc>
  <lastmod>2026-08-18T04:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミングデータからの質問応答に学習する記憶管理（Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data）</news:title>
   <news:publication_date>2026-08-18T04:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き分布を直接推定する深層回帰（Deep Distribution Regression）</news:title>
   <news:publication_date>2026-08-18T04:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-18T02:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-18T02:13:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-18T01:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像集合認識のための制約付き相互凸錐法（Constrained Mutual Convex Cone Method for Image Set Based Recognition）</news:title>
   <news:publication_date>2026-08-18T01:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-18T01:20:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特許ランドスケーピング用ディープモデル（Deep Patent Landscaping Model）</news:title>
   <news:publication_date>2026-08-18T01:20:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724373</loc>
  <lastmod>2026-08-18T01:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い監督の下でラベル依存構造を学ぶ（Learning Dependency Structures for Weak Supervision）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-18T01:19:49Z</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>2026-08-18T01:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帰属性に基づく因果分析による敵対的例の検出（Attribution-driven Causal Analysis for Detection of Adversarial Examples）</news:title>
   <news:publication_date>2026-08-18T00:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>実世界画像を「浄化」するリアルタイムスタイル転送（Purifying Naturalistic Images through a Real-time Style Transfer Semantics Network）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>f-ダイバージェンスのべき乗カイ展開（Power chi expansions of f-divergences）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724363</loc>
  <lastmod>2026-08-18T00:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習によるチーム最適化の達成（Decentralized Learning for Optimality in Stochastic Dynamic Teams and Games with Local Control and Global State Information）</news:title>
   <news:publication_date>2026-08-18T00:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724361</loc>
  <lastmod>2026-08-18T00:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続空間強化学習におけるブートストラップ応用（On Applications of Bootstrap in Continuous Space Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T00:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724359</loc>
  <lastmod>2026-08-18T00:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テクノシグネチャ探索が示す検出と非検出の意味（Searching for Technosignatures: Implications of Detection and Non-Detection）</news:title>
   <news:publication_date>2026-08-18T00:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724357</loc>
  <lastmod>2026-08-18T00:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散仮説検定とByzantine耐性に向けた新手法（A New Approach for Distributed Hypothesis Testing with Extensions to Byzantine-Resilience）</news:title>
   <news:publication_date>2026-08-18T00:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724355</loc>
  <lastmod>2026-08-17T23:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEの診断と強化 — 二段階で“生成力”を取り戻す（Diagnosing and Enhancing VAE Models）</news:title>
   <news:publication_date>2026-08-17T23:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724353</loc>
  <lastmod>2026-08-17T23:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTセキュリティにおける機械学習の現在地と課題（Machine Learning in IoT Security: Current Solutions and Future Challenges）</news:title>
   <news:publication_date>2026-08-17T23:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724351</loc>
  <lastmod>2026-08-17T23:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パララックス注意機構によるステレオ画像超解像（Learning Parallax Attention for Stereo Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-17T23:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724349</loc>
  <lastmod>2026-08-17T23:32:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間遅延座標とリザバーで作るマクロ流体モデル（MACHINE-LEARNING CONSTRUCTION OF A MODEL FOR A MACROSCOPIC FLUID VARIABLE USING THE DELAY-COORDINATE OF A SCALAR OBSERVABLE）</news:title>
   <news:publication_date>2026-08-17T23:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724347</loc>
  <lastmod>2026-08-17T23:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の運転行動の創発的性質をシミュレートする（Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning）</news:title>
   <news:publication_date>2026-08-17T23:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724345</loc>
  <lastmod>2026-08-17T23:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数空間での変分ベイズニューラルネットワーク（Functional Variational Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-17T23:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724343</loc>
  <lastmod>2026-08-17T23:31:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房組織画像による前立腺がん検出の改善（Improving Prostate Cancer Detection with Breast Histopathology Images）</news:title>
   <news:publication_date>2026-08-17T23:31:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724341</loc>
  <lastmod>2026-08-17T22:40:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPMによるフルフェイス視線推定の効率化（LPM: Learnable Pooling Module for Efficient Full-Face Gaze Estimation）</news:title>
   <news:publication_date>2026-08-17T22:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724339</loc>
  <lastmod>2026-08-17T22:39:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり特徴学習による一貫性のある対話生成（Consistent Dialogue Generation with Self-supervised Feature Learning）</news:title>
   <news:publication_date>2026-08-17T22:39:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724337</loc>
  <lastmod>2026-08-17T22:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習による固有状態位相の同定（Unsupervised Learning Eigenstate Phases of Matter）</news:title>
   <news:publication_date>2026-08-17T22:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724335</loc>
  <lastmod>2026-08-17T22:38:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>25 Orionis 群の系統初期質量関数（System IMF of the 25 Ori Group from Planetary-Mass Objects to Intermediate/High-Mass Stars）</news:title>
   <news:publication_date>2026-08-17T22:38:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724333</loc>
  <lastmod>2026-08-17T22:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知でない拘束系の軌道最適化に対する強化学習アプローチ（Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-17T22:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724331</loc>
  <lastmod>2026-08-17T22:38:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想化ネットワークデバイスにおけるオンライン機械学習を用いた基数推定（Cardinality Estimation in a Virtualized Network Device Using Online Machine Learning）</news:title>
   <news:publication_date>2026-08-17T22:38:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724329</loc>
  <lastmod>2026-08-17T22:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコードの言語モデルにおけるオープン語彙化とサブワード手法（Maybe Deep Neural Networks are the Best Choice for Modeling）</news:title>
   <news:publication_date>2026-08-17T22:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724327</loc>
  <lastmod>2026-08-17T21:46:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PointNetLKによる点群の高精度登録（PointNetLK: Robust &amp;amp; Efﬁcient Point Cloud Registration using PointNet）</news:title>
   <news:publication_date>2026-08-17T21:46:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724325</loc>
  <lastmod>2026-08-17T21:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助損失による仮説拡張の最適化（ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation）</news:title>
   <news:publication_date>2026-08-17T21:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724323</loc>
  <lastmod>2026-08-17T21:46:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多腕バンディット型MCMCが拓く二重難解事後分布のサンプリング改善（A Multi-armed Bandit MCMC, with applications in sampling from doubly intractable posterior）</news:title>
   <news:publication_date>2026-08-17T21:46:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724321</loc>
  <lastmod>2026-08-17T21:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コード検索向けに注釈を最適化するCoaCor（CoaCor: Code Annotation for Code Retrieval with Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-17T21:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724319</loc>
  <lastmod>2026-08-17T21:45:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンに人を置く：3D屋内環境におけるアフォーダンス学習（Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments）</news:title>
   <news:publication_date>2026-08-17T21:45:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724317</loc>
  <lastmod>2026-08-17T21:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の文脈でのデモ学習における不確かさ認識（Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-17T21:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724315</loc>
  <lastmod>2026-08-17T21:44:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる美学の探究（Aesthetics of Neural Network Art）</news:title>
   <news:publication_date>2026-08-17T21:44:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724313</loc>
  <lastmod>2026-08-17T20:53:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声コマンド生成におけるProgressive WaveGANの実用性（VOICE COMMAND GENERATION USING PROGRESSIVE WAVEGANS）</news:title>
   <news:publication_date>2026-08-17T20:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724311</loc>
  <lastmod>2026-08-17T20:53:07Z</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・シーン分解によるマルチ人物モーションキャプチャ（Neural Scene Decomposition for Multi-Person Motion Capture）</news:title>
   <news:publication_date>2026-08-17T20:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724309</loc>
  <lastmod>2026-08-17T20:52:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジィ・ラフセットによるフィッシング検出の特徴選択（Fuzzy Rough Set Feature Selection to Enhance Phishing Attack Detection）</news:title>
   <news:publication_date>2026-08-17T20:52:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724307</loc>
  <lastmod>2026-08-17T20:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化量子化ニューラルネットワーク学習におけるストレートスルー推定器の理解（UNDERSTANDING STRAIGHT-THROUGH ESTIMATOR IN TRAINING ACTIVATION QUANTIZED NEURAL NETS）</news:title>
   <news:publication_date>2026-08-17T20:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724305</loc>
  <lastmod>2026-08-17T20:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースで局所的に密な液体アルゴンTPCデータ向けスケーラブル深層畳み込みニューラルネットワーク（Scalable Deep Convolutional Neural Networks for Sparse, Locally Dense Liquid Argon Time Projection Chamber Data）</news:title>
   <news:publication_date>2026-08-17T20:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724303</loc>
  <lastmod>2026-08-17T20:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグバン後1ギガ年未満に形成された大量星形成銀河の個数調査（Taking Census of Massive, Star-Forming Galaxies formed </news:title>
   <news:publication_date>2026-08-17T20:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724301</loc>
  <lastmod>2026-08-17T20:51:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種ロボット間で清掃タスクを受け渡す深層学習（Cleaning tasks knowledge transfer between heterogeneous robots: a deep learning approach）</news:title>
   <news:publication_date>2026-08-17T20:51:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724299</loc>
  <lastmod>2026-08-17T19:59:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>立っている波の調和的安定性解析の新手法（Harmonic Stability of Standing Water Waves）</news:title>
   <news:publication_date>2026-08-17T19:59:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724297</loc>
  <lastmod>2026-08-17T19:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724295</loc>
  <lastmod>2026-08-17T19:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間U-Netによるグラフ時系列モデリング（ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724293</loc>
  <lastmod>2026-08-17T19:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T19:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-17T19:57:20Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T19:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T19:57:00Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>RVOSによる動画物体分割の終端間リカレントネットワーク（RVOS: End-to-End Recurrent Network for Video Object Segmentation）</news:title>
   <news:publication_date>2026-08-17T19:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T19:05:18Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>LiDAR支援による大規模ストリートビューのプライバシー保護（LiDAR-assisted Large-scale Privacy Protection in Street-view Cycloramas）</news:title>
   <news:publication_date>2026-08-17T19:05:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T19:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応スケッチによるスケーラブルなガウス過程最適化（Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret）</news:title>
   <news:publication_date>2026-08-17T19:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724277</loc>
  <lastmod>2026-08-17T19:03:34Z</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のオンライン拡張手法（Online Augmentation for Hyperspectral Data）</news:title>
   <news:publication_date>2026-08-17T19:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T19:03:22Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スプートニク平原の再配向が示すもの（Reorientation of Sputnik Planitia implies a Subsurface Ocean on Pluto）</news:title>
   <news:publication_date>2026-08-17T19:03:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724273</loc>
  <lastmod>2026-08-17T19:02:48Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>クォータニオン行列乗算の高性能実装と有効性（On the Efficacy and High-Performance Implementation of Quaternion Matrix Multiplication）</news:title>
   <news:publication_date>2026-08-17T19:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724271</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プルート表面での窒素氷対流が駆動する地質活動（Convection in a volatile nitrogen-ice-rich layer drives Pluto’s geological vigor）</news:title>
   <news:publication_date>2026-08-17T18:11:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>会話エージェント構築のためのNLUサービスベンチマーク（Benchmarking Natural Language Understanding Services for building Conversational Agents）</news:title>
   <news:publication_date>2026-08-17T18:09:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T18:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大k-プレックス問題に対する強化学習ベースの局所探索（Effective reinforcement learning based local search for the maximum k-plex problem）</news:title>
   <news:publication_date>2026-08-17T18:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724259</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T18:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面重力波伝播におけるBoussinesq成分と非Boussinesq成分の対立的役割（On the opposing roles of the Boussinesq and non-Boussinesq baroclinic torques in surface gravity wave propagation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>難易度を意識した深層距離学習（Hardness-Aware Deep Metric Learning）</news:title>
   <news:publication_date>2026-08-17T17:15:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724253</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>深層ニューラル推論過程の可視化と透明性の向上（Improving Transparency of Deep Neural Inference Process）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-17T17:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEEPOBS: 深層学習の最適化器評価を標準化する試み（DEEPOBS: A Deep Learning Optimizer Benchmark Suite）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T17:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724247</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724245</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>自律3Dトーキングアバターのアニメーション化（Animating an Autonomous 3D Talking Avatar）</news:title>
   <news:publication_date>2026-08-17T17:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724243</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724241</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>市場トレンド予測におけるセンチメント分析の実務的知見（Market Trend Prediction using Sentiment Analysis）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724239</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>資源抽象化による多エージェント渋滞問題の突破（Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems）</news:title>
   <news:publication_date>2026-08-17T16:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724237</loc>
  <lastmod>2026-08-17T16:20:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T16:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724235</loc>
  <lastmod>2026-08-17T16:20:06Z</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>2026-08-17T16:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724233</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-17T16:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン予算制約下の学習──到着データで特徴を選ぶ現場のための枠組み（Online Budgeted Learning for Classifier Induction）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人動的コスト認識センシングによる潜在コンテクスト検出（Personal Dynamic Cost-Aware Sensing for Latent Context Detection）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中移動体の動力学モデルをオンラインで学ぶ枠組み（A Framework for On-line Learning of Underwater Vehicles Dynamic Models）</news:title>
   <news:publication_date>2026-08-17T15:25:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724219</loc>
  <lastmod>2026-08-17T15:25:06Z</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>2026-08-17T15:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724217</loc>
  <lastmod>2026-08-17T15:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核のインスタンス分割を頑健化するCIA-Net（CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation）</news:title>
   <news:publication_date>2026-08-17T15:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724215</loc>
  <lastmod>2026-08-17T14:33:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索ベースの効率的な重み付きモデル積分（Efficient Search-Based Weighted Model Integration）</news:title>
   <news:publication_date>2026-08-17T14:33:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724213</loc>
  <lastmod>2026-08-17T14:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFiで群衆を数えるDeepCount（DeepCount: Crowd Counting with WiFi via Deep Learning）</news:title>
   <news:publication_date>2026-08-17T14:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724211</loc>
  <lastmod>2026-08-17T14:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル感情分類（Multimodal Emotion Classification）</news:title>
   <news:publication_date>2026-08-17T14:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724209</loc>
  <lastmod>2026-08-17T14:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JWSTによる再電離時代の探索とワイドフィールド時間領域サーベイ（JWST: Probing the Epoch of Reionization with a Wide Field Time-Domain Survey）</news:title>
   <news:publication_date>2026-08-17T14:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724207</loc>
  <lastmod>2026-08-17T14:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチジオメトリ空間音響モデリングによる遠隔音声認識の堅牢化（MULTI-GEOMETRY SPATIAL ACOUSTIC MODELING FOR DISTANT SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-08-17T14:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724205</loc>
  <lastmod>2026-08-17T14:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性情報に基づくゼロショットドメイン適応（Zero-shot Domain Adaptation Based on Attribute Information）</news:title>
   <news:publication_date>2026-08-17T14:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724203</loc>
  <lastmod>2026-08-17T14:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における最尤推定の最適性と有界凸回帰の検証（Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression）</news:title>
   <news:publication_date>2026-08-17T14:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724201</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>銀河中心研究の次の10年を描く（Envisioning the next decade of Galactic Center science）</news:title>
   <news:publication_date>2026-08-17T13:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724199</loc>
  <lastmod>2026-08-17T13:37:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河ハローの中間年齢集団の欠如（The intermediate age population of the Galactic halo）</news:title>
   <news:publication_date>2026-08-17T13:37:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724197</loc>
  <lastmod>2026-08-17T13:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数のシフトだけで十分である：効率的な畳み込みニューラルネットワーク設計（All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification）</news:title>
   <news:publication_date>2026-08-17T13:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724195</loc>
  <lastmod>2026-08-17T13:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値確率方策に対するAugment‑Reinforce‑Merge方策勾配（Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy）</news:title>
   <news:publication_date>2026-08-17T13:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724193</loc>
  <lastmod>2026-08-17T13:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生可能エネルギーの時空間シナリオ予測（Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach）</news:title>
   <news:publication_date>2026-08-17T13:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724191</loc>
  <lastmod>2026-08-17T13:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stokes流懸濁液のシミュレーション高速化（Machine learning acceleration of simulations of Stokesian suspensions）</news:title>
   <news:publication_date>2026-08-17T13:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724189</loc>
  <lastmod>2026-08-17T13:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク志向の設計を深層強化学習で実現する手法（Task-oriented Design through Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-17T13:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724187</loc>
  <lastmod>2026-08-17T12:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測に直結する特徴量ランキングの柔軟な枠組み（A flexible model-free prediction-based framework for feature ranking）</news:title>
   <news:publication_date>2026-08-17T12:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724185</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>構文を取り込む新しいSRL手法：SupertagsによるSyntax-aware Neural Semantic Role Labeling with Supertags (Syntax-aware Neural Semantic Role Labeling with Supertags)</news:title>
   <news:publication_date>2026-08-17T12:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724183</loc>
  <lastmod>2026-08-17T12:42:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoMLコンペの設計と成果（AutoML @ NeurIPS 2018 challenge: Design and Results）</news:title>
   <news:publication_date>2026-08-17T12:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724181</loc>
  <lastmod>2026-08-17T12:41:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織画像から予後を予測する無教師学習の試み（TOWARDS UNSUPERVISED CANCER SUBTYPING: PREDICTING PROGNOSIS USING A HISTOLOGIC VISUAL DICTIONARY）</news:title>
   <news:publication_date>2026-08-17T12:41:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724179</loc>
  <lastmod>2026-08-17T12:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフクラスタリングの解像度パラメータを学習する方法（Learning Resolution Parameters for Graph Clustering）</news:title>
   <news:publication_date>2026-08-17T12:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724177</loc>
  <lastmod>2026-08-17T12:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間領域における特徴集約を学習する手法（Learning Feature Aggregation in Temporal Domain for Re-Identification）</news:title>
   <news:publication_date>2026-08-17T12:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724175</loc>
  <lastmod>2026-08-17T12:41:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから実環境へゼロショットで移行する自動運転制御（Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning）</news:title>
   <news:publication_date>2026-08-17T12:41:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724173</loc>
  <lastmod>2026-08-17T11:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負ローカルスパースコーディングによるサブスペースクラスタリング（Non-Negative Local Sparse Coding for Subspace Clustering）</news:title>
   <news:publication_date>2026-08-17T11:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724171</loc>
  <lastmod>2026-08-17T11:46:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>“Hang in there”：共感的応答を要する投稿の自動検出（“Hang in there”: Lexical and visual analysis to identify posts warranting empathetic responses）</news:title>
   <news:publication_date>2026-08-17T11:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724169</loc>
  <lastmod>2026-08-17T11:39:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的にもっと自然なVRの把持（A Visually Plausible Grasping System for Object Manipulation and Interaction in Virtual Reality Environments）</news:title>
   <news:publication_date>2026-08-17T11:39:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724167</loc>
  <lastmod>2026-08-17T11:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原始星系の組み立てにおける変動性（Variability in the Assembly of Protostellar Systems）</news:title>
   <news:publication_date>2026-08-17T11:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724165</loc>
  <lastmod>2026-08-17T11:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>修正的な人間フィードバックからガウス方策を学ぶ（Learning Gaussian Policies from Corrective Human Feedback）</news:title>
   <news:publication_date>2026-08-17T11:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724163</loc>
  <lastmod>2026-08-17T11:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性を重視したカーネルスパースコーディングと辞書学習（Conﬁdent Kernel Sparse Coding and Dictionary Learning）</news:title>
   <news:publication_date>2026-08-17T11:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724161</loc>
  <lastmod>2026-08-17T11:37:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Alfvén波のチャーピングと高速イオン損失の機械学習解析（Machine learning characterisation of Alfvénic and sub-Alfvénic chirping and correlation with fast ion loss at NSTX）</news:title>
   <news:publication_date>2026-08-17T11:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724159</loc>
  <lastmod>2026-08-17T10:46:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T10:46:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ゲーム開発で学ぶプログラミング概念（Teaching Programming Concepts by Developing Games）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>継続的に学習するシステムの参照アーキテクチャ（Continual Learning in Practice）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T06:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T05:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T05:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目的指向行動と変分予測符号化による視覚注意とワーキングメモリの動的統合（Goal-Directed Behavior under Variational Predictive Coding）</news:title>
   <news:publication_date>2026-08-17T05:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724069</loc>
  <lastmod>2026-08-17T05:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴を凝縮して整列させる教師なしドメイン適応（Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation）</news:title>
   <news:publication_date>2026-08-17T05:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724067</loc>
  <lastmod>2026-08-17T05:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RFループ内での深層学習を組み込む無線機器のリアルタイム化（Big Data Goes Small: Real-Time Spectrum-Driven Embedded Wireless Networking Through Deep Learning in the RF Loop）</news:title>
   <news:publication_date>2026-08-17T05:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724065</loc>
  <lastmod>2026-08-17T05:10:09Z</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>2026-08-17T05:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724063</loc>
  <lastmod>2026-08-17T05:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歴史文書の正規化における少数例学習とゼロショット学習の実証（Few-Shot and Zero-Shot Learning for Historical Text Normalization）</news:title>
   <news:publication_date>2026-08-17T05:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724061</loc>
  <lastmod>2026-08-17T04:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程とベイズ最適化の金融応用（Financial Applications of Gaussian Processes and Bayesian Optimization）</news:title>
   <news:publication_date>2026-08-17T04:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724059</loc>
  <lastmod>2026-08-17T04:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散データにおける条件付き独立性検定（Testing Conditional Independence on Discrete Data using Stochastic Complexity）</news:title>
   <news:publication_date>2026-08-17T04:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724057</loc>
  <lastmod>2026-08-17T04:16:42Z</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>2026-08-17T04:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724055</loc>
  <lastmod>2026-08-17T04:16:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン人間行動認識に階層化隠れマルコフモデルを用いる（Online Human Activity Recognition Employing Hierarchical Hidden Markov Models）</news:title>
   <news:publication_date>2026-08-17T04:16:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724053</loc>
  <lastmod>2026-08-17T04:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アーキテクチャによる攻撃的言語分析（Offensive Language Analysis using Deep Learning Architecture）</news:title>
   <news:publication_date>2026-08-17T04:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724051</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T04:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724049</loc>
  <lastmod>2026-08-17T04:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析に基づくマルチビュー深層表現による画像分類（Image Classification base on PCA of Multi-view Deep Representation）</news:title>
   <news:publication_date>2026-08-17T04:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724047</loc>
  <lastmod>2026-08-17T03:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率の高い物体検出を実現するSpiking‑YOLO（Spiking‑YOLO: Spiking Neural Network for Energy‑Efficient Object Detection）</news:title>
   <news:publication_date>2026-08-17T03:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724045</loc>
  <lastmod>2026-08-17T03:23:41Z</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>2026-08-17T03:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724043</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T03:23:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724041</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T03:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724039</loc>
  <lastmod>2026-08-17T03:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T03:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724037</loc>
  <lastmod>2026-08-17T03:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724035</loc>
  <lastmod>2026-08-17T03:21:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識における閉塞指向コンパクトテンプレート学習（Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition）</news:title>
   <news:publication_date>2026-08-17T03:21:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724033</loc>
  <lastmod>2026-08-17T02:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T02:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724031</loc>
  <lastmod>2026-08-17T02:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724029</loc>
  <lastmod>2026-08-17T02:29:07Z</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>2026-08-17T02:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724027</loc>
  <lastmod>2026-08-17T02:28:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再プログラマブルな電気光学的非線形活性化関数（Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks）</news:title>
   <news:publication_date>2026-08-17T02:28:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724025</loc>
  <lastmod>2026-08-17T02:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的に学習するGANによる楽曲生成の実践と意義（Progressive Generative Adversarial Binary Networks for Music Generation）</news:title>
   <news:publication_date>2026-08-17T02:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724023</loc>
  <lastmod>2026-08-17T02:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランクテンソルグリッドによる画像補完（Low-rank Tensor Grid for Image Completion）</news:title>
   <news:publication_date>2026-08-17T02:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724021</loc>
  <lastmod>2026-08-17T02:28:02Z</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>2026-08-17T02:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724019</loc>
  <lastmod>2026-08-17T01:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高エネルギー物理における機械学習の適用（Machine Learning Solutions for High Energy Physics）</news:title>
   <news:publication_date>2026-08-17T01:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724017</loc>
  <lastmod>2026-08-17T01:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈対応学習によるニューラル機械翻訳（Context-Aware Learning for Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-17T01:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-17T01:32:26Z</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>2026-08-17T01:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724013</loc>
  <lastmod>2026-08-17T01:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化医用画像解析の深層学習革新（Deep Learning for Automated Medical Image Analysis）</news:title>
   <news:publication_date>2026-08-17T01:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724011</loc>
  <lastmod>2026-08-17T01:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lq安定性のための指数的エフロン–スタイン不等式（An Exponential Efron-Stein Inequality for Lq Stable Learning Rules）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724009</loc>
  <lastmod>2026-08-17T01:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実践的な多忠実度ベイズ最適化によるハイパーパラメータ探索（Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単一RGB画像から複雑トポロジーのメッシュを生成する骨格ブリッジ学習（A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images）</news:title>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724005</loc>
  <lastmod>2026-08-17T00:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移適応学習の10年サーベイ（Transfer Adaptation Learning: A Decade Survey）</news:title>
   <news:publication_date>2026-08-17T00:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724003</loc>
  <lastmod>2026-08-17T00:39:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なセマンティックセグメンテーションのための知識適応（Knowledge Adaptation for Efficient Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-17T00:39:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724001</loc>
  <lastmod>2026-08-17T00:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習によるアイス状態の生成（Generation of ice states through deep reinforcement learning）</news:title>
   <news:publication_date>2026-08-17T00:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723999</loc>
  <lastmod>2026-08-17T00:38:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングオシレーターネットワークを用いたハードウェアトロイ検出と教師あり学習の比較（Supervised Machine Learning Techniques for Trojan Detection with Ring Oscillator Network）</news:title>
   <news:publication_date>2026-08-17T00:38:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723997</loc>
  <lastmod>2026-08-17T00:38:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチクラス動的OD需要の推定（Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs）</news:title>
   <news:publication_date>2026-08-17T00:38:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723995</loc>
  <lastmod>2026-08-17T00:37:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変動する特徴量を扱う可証明学習アルゴリズム（Provably Correct Learning Algorithms in the Presence of Time-Varying Features Using a Variational Perspective）</news:title>
   <news:publication_date>2026-08-17T00:37:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723993</loc>
  <lastmod>2026-08-17T00:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低消費電力識別型深層信念ネットワークのための近似計算フレームワーク（AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks）</news:title>
   <news:publication_date>2026-08-17T00:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723991</loc>
  <lastmod>2026-08-16T23:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Log-Likelihood Ratio Quantization（Deep Log-Likelihood Ratio Quantization）</news:title>
   <news:publication_date>2026-08-16T23:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723989</loc>
  <lastmod>2026-08-16T23:45:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎化されたスパース加法モデル（Generalized Sparse Additive Models）</news:title>
   <news:publication_date>2026-08-16T23:45:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723987</loc>
  <lastmod>2026-08-16T23:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則間隔データに対するウェーブレット回帰と加法モデル（Wavelet regression and additive models for irregularly spaced data）</news:title>
   <news:publication_date>2026-08-16T23:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723985</loc>
  <lastmod>2026-08-16T22:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価バー画像を使ったCNNによるアルゴリズム取引モデル（Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T22:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723983</loc>
  <lastmod>2026-08-16T22:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LEAPによる辺性質の学習（Learning Edge Properties in Graphs from Path Aggregations）</news:title>
   <news:publication_date>2026-08-16T22:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723981</loc>
  <lastmod>2026-08-16T22:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ彩色問題とDeep Learningの邂逅（Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems）</news:title>
   <news:publication_date>2026-08-16T22:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723979</loc>
  <lastmod>2026-08-16T22:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮ビデオ品質向上のための品質ゲート付きConvLSTM（Quality-Gated Convolutional LSTM for Enhancing Compressed Video）</news:title>
   <news:publication_date>2026-08-16T22:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723977</loc>
  <lastmod>2026-08-16T22:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球近傍の超新星爆発が示す証拠と示唆（Near-Earth Supernova Explosions: Evidence, Implications, and Opportunities）</news:title>
   <news:publication_date>2026-08-16T22:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723975</loc>
  <lastmod>2026-08-16T22:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波リズムの出現：EEGデータのモデル解釈（Emergence of Brain Rhythms: Model Interpretation of EEG Data）</news:title>
   <news:publication_date>2026-08-16T22:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723973</loc>
  <lastmod>2026-08-16T21:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知の相互作用だけで薬物相互作用を予測する手法の提案（Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures）</news:title>
   <news:publication_date>2026-08-16T21:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723971</loc>
  <lastmod>2026-08-16T21:46:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノラル音声改善と認識のギャップを埋める（Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling）</news:title>
   <news:publication_date>2026-08-16T21:46:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723969</loc>
  <lastmod>2026-08-16T21:46:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助的学習による壊滅的忘却の克服（Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay）</news:title>
   <news:publication_date>2026-08-16T21:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723967</loc>
  <lastmod>2026-08-16T21:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い可逆変換で分散MCMCを速く正確にする手法（Embarrassingly parallel MCMC using deep invertible transformations）</news:title>
   <news:publication_date>2026-08-16T21:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723965</loc>
  <lastmod>2026-08-16T21:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における意図しないバイアスを多面的に測る指標群（Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification）</news:title>
   <news:publication_date>2026-08-16T21:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723963</loc>
  <lastmod>2026-08-16T21:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOGGLESによる自動画像ラベリング（GOGGLES: Automatic Image Labeling with Affinity Coding）</news:title>
   <news:publication_date>2026-08-16T21:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723961</loc>
  <lastmod>2026-08-16T21:44:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDGES低周波スペクトルにおける赤方偏移した21cm信号（THE REDSHIFTED 21-CM SIGNAL IN THE EDGES LOW-BAND SPECTRUM）</news:title>
   <news:publication_date>2026-08-16T21:44:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723959</loc>
  <lastmod>2026-08-16T20:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Seq2Seqを用いた高速Text-to-Speech（Deep Text-to-Speech System with Seq2Seq Model）</news:title>
   <news:publication_date>2026-08-16T20:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723957</loc>
  <lastmod>2026-08-16T20:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模交通信号制御のためのマルチエージェント深層強化学習（Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control）</news:title>
   <news:publication_date>2026-08-16T20:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723955</loc>
  <lastmod>2026-08-16T20:52:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NASAのSDOミッションから作られた機械学習用データセットの意義（A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission）</news:title>
   <news:publication_date>2026-08-16T20:52:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723953</loc>
  <lastmod>2026-08-16T20:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巨大衝突の現場で使える機械学習モデル（Realistic On-The-Fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts）</news:title>
   <news:publication_date>2026-08-16T20:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723951</loc>
  <lastmod>2026-08-16T20:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話と転移学習による実用的意味解析（Practical Semantic Parsing for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-08-16T20:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723949</loc>
  <lastmod>2026-08-16T20:51:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期の宇宙の相転移をLyαで解き明かす（Unveiling the Phase Transition of the Universe During the Reionization Epoch with Lyα）</news:title>
   <news:publication_date>2026-08-16T20:51:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723947</loc>
  <lastmod>2026-08-16T20:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的な変分量子計算の実現可能性（Universal Variational Quantum Computation）</news:title>
   <news:publication_date>2026-08-16T20:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723945</loc>
  <lastmod>2026-08-16T19:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小マゼラン雲の個別恒星を用いたTP-AGB段階の制約（Constraining the thermally-pulsing asymptotic giant branch phase with resolved stellar populations in the Small Magellanic Cloud）</news:title>
   <news:publication_date>2026-08-16T19:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723943</loc>
  <lastmod>2026-08-16T19:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフォールド上の行列因子分解としてのクラスタリングの再考（Revisiting clustering as matrix factorisation on the Stiefel manifold）</news:title>
   <news:publication_date>2026-08-16T19:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723941</loc>
  <lastmod>2026-08-16T19:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ割当モデル：非負テンソル分解とトピックモデルのための逐次モンテカルロ推論（Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Pólya Urns）</news:title>
   <news:publication_date>2026-08-16T19:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723939</loc>
  <lastmod>2026-08-16T19:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経剪定による継続学習（Continual Learning via Neural Pruning）</news:title>
   <news:publication_date>2026-08-16T19:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723937</loc>
  <lastmod>2026-08-16T19:47:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>conLSH：文脈を使ってノイズの多い長リードをマッピングする新しいハッシュ法（conLSH: Context based Locality Sensitive Hashing for Mapping of noisy SMRT Reads）</news:title>
   <news:publication_date>2026-08-16T19:47:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723935</loc>
  <lastmod>2026-08-16T19:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチメッセンジャー天文学の展望（Opportunities for Multimessenger Astronomy in the 2020s）</news:title>
   <news:publication_date>2026-08-16T19:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723933</loc>
  <lastmod>2026-08-16T19:47:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 1533、IC 2038、IC 2039：ドラード群の相互作用する三重銀河（VEGAS: NGC 1533, IC 2038 and IC 2039: an interacting triplet in the Dorado group）</news:title>
   <news:publication_date>2026-08-16T19:47:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723931</loc>
  <lastmod>2026-08-16T18:55:18Z</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スケーリング—キャパシティ配分の視点（Scaling up deep neural networks: a capacity allocation perspective）</news:title>
   <news:publication_date>2026-08-16T18:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723929</loc>
  <lastmod>2026-08-16T18:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的コミュニケーションにおける語用論的推論と視覚的抽象化（Pragmatic inference and visual abstraction enable contextual flexibility during visual communication）</news:title>
   <news:publication_date>2026-08-16T18:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723927</loc>
  <lastmod>2026-08-16T18:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で送信アンテナを賢く選ぶ：Massive MIMO-GSMにおける実証的改善（Transmit Antenna Selection for Massive MIMO-GSM with Machine Learning）</news:title>
   <news:publication_date>2026-08-16T18:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723925</loc>
  <lastmod>2026-08-16T18:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ニューラルネットワークの平均場解析（Mean Field Analysis of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-16T18:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723923</loc>
  <lastmod>2026-08-16T18:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M33に対する新規深部JVLA電波サーベイ（A NEW, DEEP JVLA RADIO SURVEY OF M33）</news:title>
   <news:publication_date>2026-08-16T18:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723921</loc>
  <lastmod>2026-08-16T18:53:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反応学習戦略が変える反復ゲームの設計（REACTIVE LEARNING STRATEGIES FOR ITERATED GAMES）</news:title>
   <news:publication_date>2026-08-16T18:53:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723919</loc>
  <lastmod>2026-08-16T18:53:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理知識とAIを賢く組み合わせる（Physics Enhanced Artificial Intelligence）</news:title>
   <news:publication_date>2026-08-16T18:53:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723917</loc>
  <lastmod>2026-08-16T18:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ知覚によるアフォーダンス地図の構築（Building an Affordances Map with Interactive Perception）</news:title>
   <news:publication_date>2026-08-16T18:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723915</loc>
  <lastmod>2026-08-16T17:53:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lγ-PageRankによる半教師あり学習（Lγ-PageRank for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-08-16T17:53:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723913</loc>
  <lastmod>2026-08-16T17:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子エンタングルメントスイッチの確率解析（On the Stochastic Analysis of a Quantum Entanglement Switch）</news:title>
   <news:publication_date>2026-08-16T17:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723911</loc>
  <lastmod>2026-08-16T17:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散K平均法による多様体クラスタリング（Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations）</news:title>
   <news:publication_date>2026-08-16T17:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723909</loc>
  <lastmod>2026-08-16T17:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース深層強化学習による機械の「描画学習」(Learning to Paint With Model-based Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-08-16T17:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723907</loc>
  <lastmod>2026-08-16T17:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子設計のための深層学習レビュー（Deep learning for molecular design – a review of the state of the art）</news:title>
   <news:publication_date>2026-08-16T17:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723905</loc>
  <lastmod>2026-08-16T17:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Accuracy BoosterによるCNN性能向上（Accuracy Booster: Performance Boosting using Feature Map Re-calibration）</news:title>
   <news:publication_date>2026-08-16T17:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723903</loc>
  <lastmod>2026-08-16T17:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowによるHPC評価と実運用への含意（An Evaluation of TensorFlow Performance in HPC Applications）</news:title>
   <news:publication_date>2026-08-16T17:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723901</loc>
  <lastmod>2026-08-16T17:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子エネルギー写像によるニューラルネットワークポテンシャルの検証（Atomic energy mapping of neural network potential）</news:title>
   <news:publication_date>2026-08-16T17:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723899</loc>
  <lastmod>2026-08-16T17:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SleepNetによる自動睡眠解析（SleepNet: Automated sleep analysis via dense convolutional neural network using physiological time series）</news:title>
   <news:publication_date>2026-08-16T17:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723897</loc>
  <lastmod>2026-08-16T16:58:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる関係推論とニューロモーフィック逆伝播学習（A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation）</news:title>
   <news:publication_date>2026-08-16T16:58:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723895</loc>
  <lastmod>2026-08-16T16:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベラー・ホット表現による脳波（EEG）てんかん性短時間活動の検出（Labeler-hot Detection of EEG Epileptic Transients）</news:title>
   <news:publication_date>2026-08-16T16:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723893</loc>
  <lastmod>2026-08-16T16:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>源を差し引いた宇宙赤外背景の背後にある集団（Populations behind the source-subtracted cosmic infrared background anisotropies）</news:title>
   <news:publication_date>2026-08-16T16:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723891</loc>
  <lastmod>2026-08-16T16:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>所定性能制御を用いた方策改良で時相論理タスクを満たす（Prescribed Performance Control Guided Policy Improvement for Satisfying Signal Temporal Logic Tasks）</news:title>
   <news:publication_date>2026-08-16T16:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723889</loc>
  <lastmod>2026-08-16T16:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン署名検証における多表現学習とマルチロス・スナップショットアンサンブル（Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs）</news:title>
   <news:publication_date>2026-08-16T16:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723887</loc>
  <lastmod>2026-08-16T16:05:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPMF: 信頼と嗜好の分割に基づく行列分解型推薦アルゴリズム（SPMF: A Social Trust and Preference Segmentation–based Matrix Factorization Recommendation Algorithm）</news:title>
   <news:publication_date>2026-08-16T16:05:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723885</loc>
  <lastmod>2026-08-16T16:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Recurrent Q-LearningとDeep Q-Learningの比較（Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft）</news:title>
   <news:publication_date>2026-08-16T16:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723883</loc>
  <lastmod>2026-08-16T16:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル流解析を超音波とCNNで実現する可能性（Demonstration of Vector Flow Imaging using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T16:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723881</loc>
  <lastmod>2026-08-16T16:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル保存埋め込みによる類似度学習（Similarity Learning via Kernel Preserving Embedding）</news:title>
   <news:publication_date>2026-08-16T16:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723879</loc>
  <lastmod>2026-08-16T16:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のための勾配降下ベース最適化アルゴリズム（Gradient Descent based Optimization Algorithms for Deep Learning Models Training）</news:title>
   <news:publication_date>2026-08-16T16:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723877</loc>
  <lastmod>2026-08-16T16:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manifold Mixupによる文字認識の改善（Manifold Mixup improves text recognition with CTC loss）</news:title>
   <news:publication_date>2026-08-16T16:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723875</loc>
  <lastmod>2026-08-16T15:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InceptionGCNによる疾病予測の新地平（InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction）</news:title>
   <news:publication_date>2026-08-16T15:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723873</loc>
  <lastmod>2026-08-16T15:13:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙マイクロ波背景放射のスペクトル歪みが切り拓く新たな観測窓（Spectral Distortions of the CMB as a Probe of Inflation, Recombination, Structure Formation and Particle Physics）</news:title>
   <news:publication_date>2026-08-16T15:13:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723871</loc>
  <lastmod>2026-08-16T15:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な画像補完（Pluralistic Image Completion）</news:title>
   <news:publication_date>2026-08-16T15:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723869</loc>
  <lastmod>2026-08-16T15:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散深層学習によるマルチサイトCT血腫セグメンテーションの実務的示唆（Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury）</news:title>
   <news:publication_date>2026-08-16T15:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723867</loc>
  <lastmod>2026-08-16T15:11:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的不整合と知識蒸留による単眼深度推定の改良（Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-08-16T15:11:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723865</loc>
  <lastmod>2026-08-16T15:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性から推論へ――汎用近似器の推定フレームワーク（From interpretability to inference: an estimation framework for universal approximators）</news:title>
   <news:publication_date>2026-08-16T15:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723863</loc>
  <lastmod>2026-08-16T15:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二人の大統領を分ける確率的決闘（A probabilistic duel to distinguish two presidents）</news:title>
   <news:publication_date>2026-08-16T15:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
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