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   <news:title>画像から便を識別する深層学習の試み（Augmenting Gastrointestinal Health: A Deep Learning Approach to Human Stool Recognition and Characterization in Macroscopic Images）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>TSKファジィと機械学習の機能同値性が示す実務への示唆（On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>確率的表面最適化と対数密度推定（General Probabilistic Surface Optimization and Log Density Estimation）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>ランダム条件付分布による分布的推論の体系化（The Random Conditional Distribution For Higher-Order Probabilistic Inference）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>肺内における局在化のための深層学習（Deep Learning for Localization in the Lung）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>文エンコーダーにおける社会的バイアスの測定（On Measuring Social Biases in Sentence Encoders）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Machine learningと物理科学の接点（Machine learning and the physical sciences）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Shannonエントロピーに基づく質問埋め込み（Question Embeddings Based on Shannon Entropy）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>単一画像から学習データを作る画素平均化法（A Novel Pixel-Averaging Technique for Extracting Training Data from a Single Image, Used in ML-Based Image Enlargement）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Gated Spatio-Temporal Energy Graphによる動画関係推論（Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>遺伝子発現データを用いた生存予測のトピックモデリング手法（Gene Expression based Survival Prediction for Cancer Patients – A Topic Modeling Approach）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>勝つことがすべてではない：ゲーム開発を支える知的エージェントの活用（Winning Isn’t Everything: Enhancing Game Development with Intelligent Agents）</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>量子コンピューティングの次の一手（Next Steps in Quantum Computing: Computer Science’s Role）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Geometry-Awareなカリキュラム学習による単眼視覚オドメトリの習得（Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>音楽とダンスで学ぶ具現化された意味（Learning embodied semantics via music and dance）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>グラフニューラルネットワークで学ぶロボット群の分散制御器学習 (Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks)</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>逆最適計画による空域運用学習（Inverse Optimal Planning for Air Traffic Control）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>マイクロバッチ学習における重み標準化とバッチ・チャンネル正規化（Micro-Batch Training with Batch-Channel Normalization and Weight Standardization）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DUNE-PRISMによる軽質暗黒物質探索の新戦略（Hunting On- and Off-Axis for Light Dark Matter with DUNE-PRISM）</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>ダークマター密度場からハローを描く物理的に動機付けられたニューラルネットワーク（Painting halos from cosmic density fields of dark matter with physically motivated neural networks）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>K2データにおける深層学習での系外惑星同定（Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>特徴量の依存を考慮した個別予測説明の改良（Explaining Individual Predictions When Features Are Dependent: More Accurate Approximations to Shapley Values）</news:title>
   <news:publication_date>2026-08-22T03:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ユーザー生成コンテンツの差分プライバシー表現学習（dpUGC: Learn Differentially Private Representation for User Generated Contents）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-22T02:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CODAによるスケール認識型敵対的密度適応による物体カウント改善（CODA: COUNTING OBJECTS VIA SCALE-AWARE ADVERSARIAL DENSITY ADAPTION）</news:title>
   <news:publication_date>2026-08-22T02:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725872</loc>
  <lastmod>2026-08-22T02:21:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多面的な社会的影響を深く捉える二重グラフ注意ネットワーク（Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems）</news:title>
   <news:publication_date>2026-08-22T02:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725870</loc>
  <lastmod>2026-08-22T02:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的コンテクストを用いたスケール適応型密特徴（Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation）</news:title>
   <news:publication_date>2026-08-22T02:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725868</loc>
  <lastmod>2026-08-22T02:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物から学ぶ「自己学習する知能」の枠組み（A Conceptual Bio-Inspired Framework for the Evolution of Artificial General Intelligence）</news:title>
   <news:publication_date>2026-08-22T02:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725866</loc>
  <lastmod>2026-08-22T02:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット学習に基づく人体活動認識（Few-Shot Learning-Based Human Activity Recognition）</news:title>
   <news:publication_date>2026-08-22T02:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725864</loc>
  <lastmod>2026-08-22T02:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同手-物体姿勢推定の一般化されたフィードバックループ（Generalized Feedback Loop for Joint Hand-Object Pose Estimation）</news:title>
   <news:publication_date>2026-08-22T02:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725862</loc>
  <lastmod>2026-08-22T01:28:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み強化学習のための深層オートエンコーダ活用（On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-22T01:28:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725860</loc>
  <lastmod>2026-08-22T01:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サレー市における子どもの脆弱性の可視化（Understanding Childhood Vulnerability in The City of Surrey）</news:title>
   <news:publication_date>2026-08-22T01:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725858</loc>
  <lastmod>2026-08-22T01:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LogBarrier擾乱攻撃の実践的解説 (THE LOGBARRIER ADVERSARIAL ATTACK)</news:title>
   <news:publication_date>2026-08-22T01:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725856</loc>
  <lastmod>2026-08-22T01:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>おおまかな確率的保証に基づくナッシュ均衡学習（Probably Approximately Correct Nash Equilibrium Learning）</news:title>
   <news:publication_date>2026-08-22T01:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725854</loc>
  <lastmod>2026-08-22T01:26:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一細胞アプローチによる細胞競合の解析（Single-cell approaches to cell competition: high-throughput imaging, machine learning and simulations）</news:title>
   <news:publication_date>2026-08-22T01:26:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725852</loc>
  <lastmod>2026-08-22T01:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所直交分解による高速内積探索の実務的解説（Local Orthogonal Decomposition for Maximum Inner Product Search）</news:title>
   <news:publication_date>2026-08-22T01:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725843</loc>
  <lastmod>2026-08-22T00:34:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスイッチング音声・言語処理の包括的レビュー（A Survey of Code-switched Speech and Language Processing）</news:title>
   <news:publication_date>2026-08-22T00:34:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725841</loc>
  <lastmod>2026-08-22T00:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sallyモジュールの構造と第二正規ヒルベルト係数の“ほぼ最小”ケース（ON THE STRUCTURE OF THE SALLY MODULE AND THE SECOND NORMAL HILBERT COEFFICIENT）</news:title>
   <news:publication_date>2026-08-22T00:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725839</loc>
  <lastmod>2026-08-22T00:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム対象の公正な分配について（On the fair division of a random object）</news:title>
   <news:publication_date>2026-08-22T00:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725837</loc>
  <lastmod>2026-08-22T00:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンゴ葉の病害識別のための領域注目型深層畳み込みニューラルネットワーク（Apple Leaf Disease Identification through Region-of-Interest-Aware Deep Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-22T00:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725835</loc>
  <lastmod>2026-08-22T00:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識CNNの雑音耐性トレーニングパラダイム（Noise-Tolerant Paradigm for Training Face Recognition CNNs）</news:title>
   <news:publication_date>2026-08-22T00:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725833</loc>
  <lastmod>2026-08-22T00:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形システム同定のサンプル複雑度下限（Sample Complexity Lower Bounds for Linear System Identification）</news:title>
   <news:publication_date>2026-08-22T00:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725831</loc>
  <lastmod>2026-08-22T00:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測・ノイズ下でカオス的力学を学習するEM様手法（EM-like Learning Chaotic Dynamics from Noisy and Partial Observations）</news:title>
   <news:publication_date>2026-08-22T00:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725829</loc>
  <lastmod>2026-08-21T23:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配ハミルトニアンモンテカルロによる非凸最適化の収束解析（Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning）</news:title>
   <news:publication_date>2026-08-21T23:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725827</loc>
  <lastmod>2026-08-21T23:38:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合デモンストレーションからのマルチモーダル方策学習（Learning a Multi-Modal Policy via Imitating Demonstrations with Mixed Behaviors）</news:title>
   <news:publication_date>2026-08-21T23:38:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725825</loc>
  <lastmod>2026-08-21T23:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>降水パラメータ化のデータ駆動アプローチ（A Data-Driven Approach to Precipitation Parameterizations Using Convolutional Encoder-Decoder Neural Networks）</news:title>
   <news:publication_date>2026-08-21T23:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725823</loc>
  <lastmod>2026-08-21T23:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策論争における内生的連携形成（Endogenous Coalition Formation in Policy Debates）</news:title>
   <news:publication_date>2026-08-21T23:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725821</loc>
  <lastmod>2026-08-21T23:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数のセンサーとアクチュエータで知覚と制御を成し遂げる考え方（Perceptual Control with Large Feature and Actuator Networks）</news:title>
   <news:publication_date>2026-08-21T23:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725819</loc>
  <lastmod>2026-08-21T23:37:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主に非循環有向ネットワークの地平線ダイナミクス（Network Horizon Dynamics I: Qualitative Aspects）</news:title>
   <news:publication_date>2026-08-21T23:37:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725817</loc>
  <lastmod>2026-08-21T22:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MetaPruningによる自動チャネルプルーニング（MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning）</news:title>
   <news:publication_date>2026-08-21T22:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725815</loc>
  <lastmod>2026-08-21T22:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>呼吸位相検出のための畳み込みニューラルネットワーク（Convolutional neural network for breathing phase detection in lung sounds）</news:title>
   <news:publication_date>2026-08-21T22:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725813</loc>
  <lastmod>2026-08-21T22:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的特徴から学ぶ少数ショット分類（Learning from Adversarial Features for Few-Shot Classification）</news:title>
   <news:publication_date>2026-08-21T22:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725811</loc>
  <lastmod>2026-08-21T22:44:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ機械振動子のレーザー冷却でゼロ点エネルギーへ到達（Laser cooling of a nanomechanical oscillator to the zero-point energy）</news:title>
   <news:publication_date>2026-08-21T22:44:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725809</loc>
  <lastmod>2026-08-21T22:44:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期言語発達の計算論的・ロボティクスモデルの概観（Computational and Robotic Models of Early Language Development: A Review）</news:title>
   <news:publication_date>2026-08-21T22:44:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725807</loc>
  <lastmod>2026-08-21T22:43:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを前提にしたベクトル空間の整列（Aligning Vector-spaces with Noisy Supervised Lexicons）</news:title>
   <news:publication_date>2026-08-21T22:43:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725805</loc>
  <lastmod>2026-08-21T21:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度への道：機械学習で加速するシリコンのab initioシミュレーション（The road to accuracy: machine-learning-accelerated silicon ab initio simulations）</news:title>
   <news:publication_date>2026-08-21T21:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725803</loc>
  <lastmod>2026-08-21T21:52:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフォールド基準で導く転移学習（Manifold Criterion Guided Transfer Learning）</news:title>
   <news:publication_date>2026-08-21T21:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725801</loc>
  <lastmod>2026-08-21T21:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化敵対的訓練による堅牢なニューラルネットワーク（Robust Neural Networks using Randomized Adversarial Training）</news:title>
   <news:publication_date>2026-08-21T21:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725799</loc>
  <lastmod>2026-08-21T21:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイルのエントロピー信号と機械学習による電子文書内悪性コードの検出（Capturing the symptoms of malicious code in electronic documents by file’s entropy signal combined with Machine learning）</news:title>
   <news:publication_date>2026-08-21T21:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725797</loc>
  <lastmod>2026-08-21T21:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から顔を生成する技術の要点（WAV2PIX: SPEECH-CONDITIONED FACE GENERATION USING GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-08-21T21:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725795</loc>
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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>2026-08-21T21:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T21:51:07Z</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>2026-08-21T21:51:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-21T21:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LOGAN: 潜在的過完備空間における非対応形状変換（LOGAN: Unpaired Shape Transform in Latent Overcomplete Space）</news:title>
   <news:publication_date>2026-08-21T21:00:19Z</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>2026-08-21T21:00:05Z</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>DeepRED: Deep Image PriorとREDを組み合わせた画像逆問題の新展開（DeepRED: Deep Image Prior Powered by RED）</news:title>
   <news:publication_date>2026-08-21T20:59:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725785</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>学習されたカーネルを用いるダウンスケーリングによる非均一単一画像のデブラー（Down-Scaling with Learned Kernels in Multi-Scale Deep Neural Networks for Non-Uniform Single Image Deblurring）</news:title>
   <news:publication_date>2026-08-21T20:59:23Z</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>空間減衰文脈による顕著物体検出の統合的手法（SAC-Net: Spatial Attenuation Context for Salient Object Detection）</news:title>
   <news:publication_date>2026-08-21T20:59:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725781</loc>
  <lastmod>2026-08-21T20:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波で指の個別動作を読み取るためのアンサンブル学習（An Ensemble Learning Based Classification of Individual Finger Movement from EEG）</news:title>
   <news:publication_date>2026-08-21T20:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725779</loc>
  <lastmod>2026-08-21T20:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層無監督ドメイン適応の高速化（Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning）</news:title>
   <news:publication_date>2026-08-21T20:58:51Z</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>周期的アニーリングスケジュールによるKL消失の抑制（Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing）</news:title>
   <news:publication_date>2026-08-21T20:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725775</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>ImageNetの学習済み分類層を活かす転移学習の再考（Enhanced Transfer Learning with ImageNet Trained Classification Layer）</news:title>
   <news:publication_date>2026-08-21T19:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725773</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>タスク特化型埋め込み変換とアテンションネットワークによる複数の人口統計属性予測（Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network）</news:title>
   <news:publication_date>2026-08-21T19:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725771</loc>
  <lastmod>2026-08-21T19:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習とセグメンテーション情報をGANで組み合わせた学習データ非依存の画像登録（COMBINING TRANSFER LEARNING AND SEGMENTATION INFORMATION WITH GANS FOR TRAINING DATA INDEPENDENT IMAGE REGISTRATION）</news:title>
   <news:publication_date>2026-08-21T19:55:56Z</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>2026-08-21T19:55:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725767</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>Iris R-CNNによる非協調環境下の虹彩分割（Iris R-CNN: Accurate Iris Segmentation in Non-cooperative Environment）</news:title>
   <news:publication_date>2026-08-21T19:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725765</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>任意ショット学習のための特徴生成フレームワーク（f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning）</news:title>
   <news:publication_date>2026-08-21T19:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T19:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種表現で言語と知識をつなぐ手法（Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction）</news:title>
   <news:publication_date>2026-08-21T19:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725761</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>サイクル一貫性を用いた画像→キャプションのエンドツーエンド学習（End-to-End Learning Using Cycle Consistency for Image-to-Caption Transformations）</news:title>
   <news:publication_date>2026-08-21T18:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T18:52:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像報告の知識駆動型自動生成（Knowledge-driven Encode, Retrieve, Paraphrase）</news:title>
   <news:publication_date>2026-08-21T18:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725757</loc>
  <lastmod>2026-08-21T18:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次のKolmogorov–Smirnov検定（A Higher-Order Kolmogorov-Smirnov Test）</news:title>
   <news:publication_date>2026-08-21T18:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725755</loc>
  <lastmod>2026-08-21T18:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差非局所注意ネットワークによる画像復元（Residual Non-Local Attention Networks for Image Restoration）</news:title>
   <news:publication_date>2026-08-21T18:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725753</loc>
  <lastmod>2026-08-21T18:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>査読理解のための論証マイニング（Argument Mining for Understanding Peer Reviews）</news:title>
   <news:publication_date>2026-08-21T18:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725751</loc>
  <lastmod>2026-08-21T18:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気共鳻画像再構成のための変換学習（Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks）</news:title>
   <news:publication_date>2026-08-21T18:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725749</loc>
  <lastmod>2026-08-21T18:00:02Z</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>2026-08-21T18:00:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725747</loc>
  <lastmod>2026-08-21T17:59:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真のバッチ弟子学習と深層サクセッサーフィーチャー（Truly Batch Apprenticeship Learning with Deep Successor Features）</news:title>
   <news:publication_date>2026-08-21T17:59:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725745</loc>
  <lastmod>2026-08-21T17:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ジャンプ線形系の安全な学習ベース制御（Safe Learning-Based Control of Stochastic Jump Linear Systems: a Distributionally Robust Approach）</news:title>
   <news:publication_date>2026-08-21T17:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725743</loc>
  <lastmod>2026-08-21T17:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス組織病理画像分類のための畳み込みニューラルネットワーク（Convolutional Neural Networks for Multi-class Histopathology Image Classification）</news:title>
   <news:publication_date>2026-08-21T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725741</loc>
  <lastmod>2026-08-21T17:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lasso Weighted k-meansが示す高次元クラスタリングの新基準（A Strongly Consistent Sparse k-means Clustering with Direct l1 Penalization on Variable Weights）</news:title>
   <news:publication_date>2026-08-21T17:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725739</loc>
  <lastmod>2026-08-21T17:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNet型畳み込みニューラルネットワークの近似と非パラメトリック推定（Approximation and Non-parametric Estimation of ResNet-type Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-21T17:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725737</loc>
  <lastmod>2026-08-21T17:06:17Z</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堅牢性の形式化（A Formalization of Robustness for Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-21T17:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725735</loc>
  <lastmod>2026-08-21T17:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-means初期化の一般化（Generalization of k-means Related Algorithms）</news:title>
   <news:publication_date>2026-08-21T17:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T17:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データと半教師あり学習で小規模・不均衡データを活用する手法（Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets）</news:title>
   <news:publication_date>2026-08-21T17:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T17:04:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>持続的気象パターン予測のための混合エキスパートモデル（A mixture of experts model for predicting persistent weather patterns）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T17:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的部分グラフ学習によるネットワーク状態予測（Discriminative Subgraph Learning via Sparse Self-Representation）</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>SNR適応型ID-OCTAによる血管可視化の精度向上（SNR-adaptive ID-OCTA）</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>
  <loc>https://aibr.jp/archives/725723</loc>
  <lastmod>2026-08-21T16:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルによる近似クエリ処理（Approximate Query Processing for Data Exploration using Deep Generative Models）</news:title>
   <news:publication_date>2026-08-21T16:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725721</loc>
  <lastmod>2026-08-21T16:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル認識型関数混合ネットワークによる分光超解像（Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution）</news:title>
   <news:publication_date>2026-08-21T16:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725719</loc>
  <lastmod>2026-08-21T16:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多属性選択率推定における深層学習の応用（Multi-Attribute Selectivity Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-08-21T16:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725717</loc>
  <lastmod>2026-08-21T16:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階圧縮によるニューラルネットワークの効率化（MUSCO: Multi-Stage Compression of neural networks）</news:title>
   <news:publication_date>2026-08-21T16:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725715</loc>
  <lastmod>2026-08-21T16:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木星の大赤斑の深さを探る（Determining the depth of Jupiter’s Great Red Spot with Juno: a Slepian approach）</news:title>
   <news:publication_date>2026-08-21T16:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725713</loc>
  <lastmod>2026-08-21T16:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ整列を教師で促す手法（Cluster Alignment with a Teacher for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-08-21T16:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725711</loc>
  <lastmod>2026-08-21T16:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高変形ソフト粒子の圧縮挙動とジャミング後の力学（Soft grain compression: beyond the jamming point）</news:title>
   <news:publication_date>2026-08-21T16:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725709</loc>
  <lastmod>2026-08-21T15:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深海面における非相互作用重力波の理論的展開（Non-interacting gravity waves on the surface of a deep fluid）</news:title>
   <news:publication_date>2026-08-21T15:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725707</loc>
  <lastmod>2026-08-21T15:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者抽出ニューラルネットワークの最適化（Optimization of Speaker Extraction Neural Network with Magnitude and Temporal Spectrum Approximation Loss）</news:title>
   <news:publication_date>2026-08-21T15:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725705</loc>
  <lastmod>2026-08-21T15:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な製品埋め込みに基づく深層レコメンダーエンジン（Deep recommender engine based on efficient product embeddings neural pipeline）</news:title>
   <news:publication_date>2026-08-21T15:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725703</loc>
  <lastmod>2026-08-21T15:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間量子化を用いた変分推論による敵対的耐性（Variational Inference with Latent Space Quantization for Adversarial Resilience）</news:title>
   <news:publication_date>2026-08-21T15:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725701</loc>
  <lastmod>2026-08-21T15:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAXMLNetが示す極端多ラベル分類の新潮流（HAXMLNet: Hierarchical Attention Network for Extreme Multi-Label Text Classification）</news:title>
   <news:publication_date>2026-08-21T15:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725699</loc>
  <lastmod>2026-08-21T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床テキストにおける最短依存経路ベースのLSTMによる関係抽出（Relation extraction between the clinical entities based on the shortest dependency path based LSTM）</news:title>
   <news:publication_date>2026-08-21T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725697</loc>
  <lastmod>2026-08-21T15:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約生成を特徴量化してフェイクニュース検出を改善する手法（Neural Abstractive Text Summarization and Fake News Detection）</news:title>
   <news:publication_date>2026-08-21T15:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725695</loc>
  <lastmod>2026-08-21T14:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB画像を入力とするマップレスロボット航法のサンプル効率化（Using RGB Image as Visual Input for Mapless Robot Navigation）</news:title>
   <news:publication_date>2026-08-21T14:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725693</loc>
  <lastmod>2026-08-21T14:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルセンサの弱ラベルデータから活動を見つける注意機構CNN（Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors）</news:title>
   <news:publication_date>2026-08-21T14:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725691</loc>
  <lastmod>2026-08-21T14:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限仮説クラス下のオンライン学習における改善された誤り境界（Algorithms and Improved bounds for online learning under finite hypothesis class）</news:title>
   <news:publication_date>2026-08-21T14:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725689</loc>
  <lastmod>2026-08-21T14:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KPTransferによるキーポイント部分集合間ドメイン転移の実用的意義（KPTransfer: improved performance and faster convergence from keypoint subset-wise domain transfer in human pose estimation）</news:title>
   <news:publication_date>2026-08-21T14:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725687</loc>
  <lastmod>2026-08-21T14:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SRGAN: トレーニングデータが結果を決める（SRGAN: Training Dataset Matters）</news:title>
   <news:publication_date>2026-08-21T14:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725685</loc>
  <lastmod>2026-08-21T14:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素値PolSARデータの効率的利用—マルチタスク深層学習フレームワーク（Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework）</news:title>
   <news:publication_date>2026-08-21T14:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725683</loc>
  <lastmod>2026-08-21T14:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散機械学習ジョブのオーケストレーションを実現するTonY（TonY: An Orchestrator for Distributed Machine Learning Jobs）</news:title>
   <news:publication_date>2026-08-21T14:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725680</loc>
  <lastmod>2026-08-21T13:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>sharpDARTS：より高速で高精度なDifferentiable Architecture Search（sharpDARTS: Faster and More Accurate Differentiable Architecture Search）</news:title>
   <news:publication_date>2026-08-21T13:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725678</loc>
  <lastmod>2026-08-21T13:29:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散再帰型オートエンコーダによる拡張可能な画像圧縮（DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression）</news:title>
   <news:publication_date>2026-08-21T13:29:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725676</loc>
  <lastmod>2026-08-21T13:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換に応答する表現の教師なし学習（AVT: Unsupervised Learning of Transformation-Equivariant Representations by Autoencoding Variational Transformations）</news:title>
   <news:publication_date>2026-08-21T13:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725674</loc>
  <lastmod>2026-08-21T13:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実環境向けの長距離ニューラル航行ポリシー（Long Range Neural Navigation Policies for the Real World）</news:title>
   <news:publication_date>2026-08-21T13:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725672</loc>
  <lastmod>2026-08-21T13:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時相論理に導かれた安全強化学習と制御バリア関数（Temporal Logic Guided Safe Reinforcement Learning Using Control Barrier Functions）</news:title>
   <news:publication_date>2026-08-21T13:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725670</loc>
  <lastmod>2026-08-21T13:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺結節検出のためのエンドツーエンド統合フレームワーク（AN END-TO-END FRAMEWORK FOR INTEGRATED PULMONARY NODULE DETECTION AND FALSE POSITIVE REDUCTION）</news:title>
   <news:publication_date>2026-08-21T13:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725668</loc>
  <lastmod>2026-08-21T13:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺葉自動分割における深層学習の実用化可能性（AUTOMATIC PULMONARY LOBE SEGMENTATION USING DEEP LEARNING）</news:title>
   <news:publication_date>2026-08-21T13:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725666</loc>
  <lastmod>2026-08-21T12:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StartNet：ストリーミング映像における行動開始検出の実時間化（StartNet: Online Detection of Action Start in Untrimmed Videos）</news:title>
   <news:publication_date>2026-08-21T12:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725664</loc>
  <lastmod>2026-08-21T12:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー学習器に対するデータ汚染攻撃と防御（Data Poisoning against Differentially-Private Learners: Attacks and Defenses）</news:title>
   <news:publication_date>2026-08-21T12:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725662</loc>
  <lastmod>2026-08-21T12:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン最適化による学習と制御の新枠組み（Online Optimisation for Online Learning and Control – From No-Regret to Generalised Error Convergence）</news:title>
   <news:publication_date>2026-08-21T12:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725660</loc>
  <lastmod>2026-08-21T12:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協働型言語学習SNSにおける書記能力評価の提案（Toward the Evaluation of Written Proficiency on a Collaborative Social Network for Learning Languages: Yask）</news:title>
   <news:publication_date>2026-08-21T12:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725658</loc>
  <lastmod>2026-08-21T12:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能力に基づくカリキュラム学習で変わる機械翻訳の学習効率（Competence-based Curriculum Learning for Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-21T12:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725656</loc>
  <lastmod>2026-08-21T12:35:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星とブラックホールの時間領域研究：X線によるコンパクト天体の同定（Time Domain Studies of Neutron Star and Black Hole Populations: X-ray Identification of Compact Object Types）</news:title>
   <news:publication_date>2026-08-21T12:35:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725654</loc>
  <lastmod>2026-08-21T12:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高効率4接合太陽電池の設計と評価（Novel High Efficiency Quadruple Junction Solar Cell with Current Matching and Quantum Efficiency Simulations）</news:title>
   <news:publication_date>2026-08-21T12:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725652</loc>
  <lastmod>2026-08-21T11:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HouseExpo：学習ベースの移動ロボット研究を加速する大規模2D室内レイアウトデータセット（HouseExpo: A Large-scale 2D Indoor Layout Dataset for Learning-based Algorithms on Mobile Robots）</news:title>
   <news:publication_date>2026-08-21T11:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725650</loc>
  <lastmod>2026-08-21T11:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による時間位相アンラッピング（Temporal phase unwrapping using deep learning）</news:title>
   <news:publication_date>2026-08-21T11:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725648</loc>
  <lastmod>2026-08-21T11:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルな差分プライバシーと認証付き堅牢性を両立する手法（Scalable Differential Privacy with Certified Robustness in Adversarial Learning）</news:title>
   <news:publication_date>2026-08-21T11:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725646</loc>
  <lastmod>2026-08-21T11:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像の疾患情報を残す意味的ノイズ除去（Semantic denoising autoencoders for retinal optical coherence tomography）</news:title>
   <news:publication_date>2026-08-21T11:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725644</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>知識に基づく応答生成の深化（Knowledge-Grounded Response Generation with Deep Attentional Latent-Variable Model）</news:title>
   <news:publication_date>2026-08-21T11:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725642</loc>
  <lastmod>2026-08-21T11:41:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィードバックネットワークによる画像超解像の新展開（Feedback Network for Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-21T11:41:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725640</loc>
  <lastmod>2026-08-21T11:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料間の類似度測定と「Distinctiveness」の重視（Measuring the Similarity between Materials with an Emphasis on the Materials’ Distinctiveness）</news:title>
   <news:publication_date>2026-08-21T11:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725638</loc>
  <lastmod>2026-08-21T10:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coin.AIによる有用作業の証明スキーム（Coin.AI: A Proof-of-Useful-Work Scheme for Blockchain-Based Distributed Deep Learning）</news:title>
   <news:publication_date>2026-08-21T10:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725636</loc>
  <lastmod>2026-08-21T10:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BitSplit-Netによるマルチビット深層ニューラルネットワーク (BitSplit-Net: Multi-bit Deep Neural Network with Bitwise Activation Function)</news:title>
   <news:publication_date>2026-08-21T10:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725634</loc>
  <lastmod>2026-08-21T10:48:38Z</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>2026-08-21T10:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725632</loc>
  <lastmod>2026-08-21T10:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動による予測保全と不確実性推定（Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models）</news:title>
   <news:publication_date>2026-08-21T10:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725630</loc>
  <lastmod>2026-08-21T10:47:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネットが変える市場調査と意思決定（Role of the internet in marketing research and business decision-making）</news:title>
   <news:publication_date>2026-08-21T10:47:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725628</loc>
  <lastmod>2026-08-21T10:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値分類における半準パラメトリックな不確かさ境界（Semi-Parametric Uncertainty Bounds for Binary Classification）</news:title>
   <news:publication_date>2026-08-21T10:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725626</loc>
  <lastmod>2026-08-21T10:47:16Z</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>2026-08-21T10:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725624</loc>
  <lastmod>2026-08-21T09:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Auto-ReID: 人物再識別向け部分認識ConvNetを自動探索する手法（Auto-ReID: Searching for a Part-Aware ConvNet for Person Re-Identification）</news:title>
   <news:publication_date>2026-08-21T09:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725622</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>進展的DNN圧縮：ADMMを用いた超高率の重み剪定と量子化の実現（Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM）</news:title>
   <news:publication_date>2026-08-21T09:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725620</loc>
  <lastmod>2026-08-21T09:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な水中画像強調による視覚認知の改善（Fast Underwater Image Enhancement for Improved Visual Perception）</news:title>
   <news:publication_date>2026-08-21T09:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T09:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律操作のためのシーン理解と深層学習（Scene Understanding for Autonomous Manipulation with Deep Learning）</news:title>
   <news:publication_date>2026-08-21T09:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725616</loc>
  <lastmod>2026-08-21T09:53:18Z</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>
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  <lastmod>2026-08-21T09:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TTRに基づく報酬で学ぶ強化学習（TTR-Based Reward for Reinforcement Learning with Implicit Model Priors）</news:title>
   <news:publication_date>2026-08-21T09:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725612</loc>
  <lastmod>2026-08-21T09:52:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PMLによるクラウド向け汎用アクセス制御言語の提案（PML: An Interpreter-Based Access Control Policy Language for Web Services）</news:title>
   <news:publication_date>2026-08-21T09:52:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725610</loc>
  <lastmod>2026-08-21T09:01:06Z</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>2026-08-21T09:01:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725608</loc>
  <lastmod>2026-08-21T09:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual Pyramid Learningによるシングルショット分割の実務的示唆（Residual Pyramid Learning for Single-Shot Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-21T09:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725606</loc>
  <lastmod>2026-08-21T09:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルシフト下の正則化学習がもたらす実務的価値（Regularized Learning for Domain Adaptation under Label Shifts）</news:title>
   <news:publication_date>2026-08-21T09:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725604</loc>
  <lastmod>2026-08-21T08:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの欠損値補完（Imputation in time series）</news:title>
   <news:publication_date>2026-08-21T08:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725602</loc>
  <lastmod>2026-08-21T08:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数クラスの生成的過剰サンプリング（Generative Adversarial Minority Oversampling）</news:title>
   <news:publication_date>2026-08-21T08:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725600</loc>
  <lastmod>2026-08-21T08:59:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般人向けの強化学習説明の実証研究（Explaining Reinforcement Learning to Mere Mortals: An Empirical Study）</news:title>
   <news:publication_date>2026-08-21T08:59:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725598</loc>
  <lastmod>2026-08-21T08:58:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家知識を組み込む機械学習（Expert-Augmented Machine Learning）</news:title>
   <news:publication_date>2026-08-21T08:58:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725596</loc>
  <lastmod>2026-08-21T08:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック回帰を用いた強化学習の価値関数構築（Symbolic Regression Methods for Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-21T08:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725594</loc>
  <lastmod>2026-08-21T08:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河から塵（ほこり）はどう逃げるのか（How does dust escape galaxies?）</news:title>
   <news:publication_date>2026-08-21T08:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725592</loc>
  <lastmod>2026-08-21T08:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CUR分解とその摂動解析が示す低ランク行列近似の安定性（CUR Decompositions, Approximations, and Perturbations）</news:title>
   <news:publication_date>2026-08-21T08:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725590</loc>
  <lastmod>2026-08-21T08:06:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布系状態推定のための物理認識ニューラルネットワーク（Physics-Aware Neural Networks for Distribution System State Estimation）</news:title>
   <news:publication_date>2026-08-21T08:06:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725588</loc>
  <lastmod>2026-08-21T08:06:07Z</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>2026-08-21T08:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T08:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能プログラミングによるテンソルネットワーク最適化（Differentiable Programming Tensor Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T08:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン深層学習のためのデータ拡張（Data Augmentation for Bayesian Deep Learning）</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>
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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>2026-08-21T07:13:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725578</loc>
  <lastmod>2026-08-21T07:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GroomRLによるジェットグルーミングの強化学習化（GroomRL: Jet Grooming through Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-21T07:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725576</loc>
  <lastmod>2026-08-21T07:12:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fog Roboticsによるロボット学習と表面片付けの実用化（A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering）</news:title>
   <news:publication_date>2026-08-21T07:12:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725574</loc>
  <lastmod>2026-08-21T07:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライ学習で得られる機械学習力場によるハイブリッドペロブスカイトの相転移（Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on-the-fly with Bayesian inference）</news:title>
   <news:publication_date>2026-08-21T07:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725572</loc>
  <lastmod>2026-08-21T07:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者に依存しない表現を学習するための敵対的手法（TOWARDS ADVERSARIAL LEARNING OF SPEAKER-INVARIANT REPRESENTATION FOR SPEECH EMOTION RECOGNITION）</news:title>
   <news:publication_date>2026-08-21T07:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725570</loc>
  <lastmod>2026-08-21T07:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間に聞き取れない音声敵対的事例の構築と堅牢化（Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-08-21T07:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725568</loc>
  <lastmod>2026-08-21T06:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手持ちWEMIを用いた目標検出アルゴリズムの比較（Comparison of Hand-held WEMI Target Detection Algorithms）</news:title>
   <news:publication_date>2026-08-21T06:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725566</loc>
  <lastmod>2026-08-21T06:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限エネルギー空間と測度論的ラプラシアンの整理（LAPLACE OPERATORS IN FINITE ENERGY AND DISSIPATION SPACES）</news:title>
   <news:publication_date>2026-08-21T06:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725564</loc>
  <lastmod>2026-08-21T06:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Monte Carlo Neural Fictitious Self-Playによる不完全情報ゲームの近似ナッシュ均衡獲得（Monte Carlo Neural Fictitious Self-Play）</news:title>
   <news:publication_date>2026-08-21T06:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725562</loc>
  <lastmod>2026-08-21T06:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非マルコフ確率過程に対する機械学習によるメモリカーネルの閉じ込み (Machine learning memory kernels as closure for non-Markovian stochastic processes)</news:title>
   <news:publication_date>2026-08-21T06:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725560</loc>
  <lastmod>2026-08-21T06:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜疾患の同時自動検出を目指した深層学習システムの評価 (Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration)</news:title>
   <news:publication_date>2026-08-21T06:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725558</loc>
  <lastmod>2026-08-21T06:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化文書における表理解（Table understanding in structured documents）</news:title>
   <news:publication_date>2026-08-21T06:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725556</loc>
  <lastmod>2026-08-21T06:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習手法で宇宙線反陽子フラックスにおけるダークマター信号を探る（Investigating the dark matter signal in the cosmic ray antiproton flux with the machine learning method）</news:title>
   <news:publication_date>2026-08-21T06:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725554</loc>
  <lastmod>2026-08-21T05:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的な強化学習による二足歩行スキル設計（Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie）</news:title>
   <news:publication_date>2026-08-21T05:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725552</loc>
  <lastmod>2026-08-21T05:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似した形態特徴を持つ細胞の識別におけるゴーストサイトメトリーの応用 (Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic Characteristics)</news:title>
   <news:publication_date>2026-08-21T05:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725550</loc>
  <lastmod>2026-08-21T05:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力市場におけるリスク最小化の機械学習アプローチ（A Machine Learning approach to Risk Minimisation in Electricity Markets with Coregionalized Sparse Gaussian Processes）</news:title>
   <news:publication_date>2026-08-21T05:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725548</loc>
  <lastmod>2026-08-21T05:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁化ダイナミクスを学習する（Learning magnetization dynamics）</news:title>
   <news:publication_date>2026-08-21T05:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725546</loc>
  <lastmod>2026-08-21T05:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体系のエンタングルメント深度を装置非依存に評価する手法の最適化（Optimization of device-independent witnesses of entanglement depth from two-body correlators）</news:title>
   <news:publication_date>2026-08-21T05:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725544</loc>
  <lastmod>2026-08-21T05:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全確率的制御の感度と安全性（Sensitivity and safety of fully probabilistic control）</news:title>
   <news:publication_date>2026-08-21T05:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725542</loc>
  <lastmod>2026-08-21T05:22:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性の目に見えない力（The invisible power of fairness. How machine learning shapes democracy）</news:title>
   <news:publication_date>2026-08-21T05:22:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725540</loc>
  <lastmod>2026-08-21T04:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OODIDAによる分散データ分析の迅速なプロトタイピング（Facilitating Rapid Prototyping in the Distributed Data Analytics Platform OODIDA via Active-Code Replacement）</news:title>
   <news:publication_date>2026-08-21T04:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725538</loc>
  <lastmod>2026-08-21T04:31:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小売の多次元売上に対する最適結合予測（Optimal Combination Forecasts on Retail Multi-Dimensional Sales Data）</news:title>
   <news:publication_date>2026-08-21T04:31:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725536</loc>
  <lastmod>2026-08-21T04:30:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Aggregated Deep Local Featuresによるリモートセンシング画像検索の合理化（Aggregated Deep Local Features for Remote Sensing Image Retrieval）</news:title>
   <news:publication_date>2026-08-21T04:30:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725534</loc>
  <lastmod>2026-08-21T04:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固体・真空界面におけるイオン液体の構造と拡散挙動に関する分子動力学シミュレーションの知見（Insights from Molecular Dynamics Simulations on Structural Organization and Diffusive Dynamics of an Ionic Liquid at Solid and Vacuum Interfaces）</news:title>
   <news:publication_date>2026-08-21T04:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725532</loc>
  <lastmod>2026-08-21T04:29:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄膜金属の結晶核の構造と形態（Structure and Morphology of Crystalline Nuclei arising in a Crystallizing Liquid Metallic Film）</news:title>
   <news:publication_date>2026-08-21T04:29:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725530</loc>
  <lastmod>2026-08-21T04:29:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透過壁環境での前面レーダー画像の歪みを軽減するノイズ除去オートエンコーダ（Mitigation of Through-Wall Distortions of Frontal Radar Images using Denoising Autoencoders）</news:title>
   <news:publication_date>2026-08-21T04:29:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725528</loc>
  <lastmod>2026-08-21T04:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓画像解析における分離表現学習（Disentangled representation learning in cardiac image analysis）</news:title>
   <news:publication_date>2026-08-21T04:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725526</loc>
  <lastmod>2026-08-21T03:37:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストクラスタリングのエンドツーエンドニューラルネットワークフレームワーク (An end-to-end Neural Network Framework for Text Clustering)</news:title>
   <news:publication_date>2026-08-21T03:37:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725524</loc>
  <lastmod>2026-08-21T03:37:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチベイズ最適化のための獲得関数サンプリング（Sampling Acquisition Functions for Batch Bayesian Optimization）</news:title>
   <news:publication_date>2026-08-21T03:37:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725522</loc>
  <lastmod>2026-08-21T03:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金属スクラップ選別にAIを持ち込む（ARTIFICIAL INTELLIGENCE-BASED PROCESS FOR METAL SCRAP SORTING）</news:title>
   <news:publication_date>2026-08-21T03:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725520</loc>
  <lastmod>2026-08-21T03:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延シナプス可塑性で学ぶ（Learning with Delayed Synaptic Plasticity）</news:title>
   <news:publication_date>2026-08-21T03:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725518</loc>
  <lastmod>2026-08-21T03:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群レベルfMRI解析のための制約付きICA‑EMDモデル (A constrained ICA-EMD Model for Group Level fMRI Analysis)</news:title>
   <news:publication_date>2026-08-21T03:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725516</loc>
  <lastmod>2026-08-21T03:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化を用いた高速ベイズ的不確実性推定と低減（Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network）</news:title>
   <news:publication_date>2026-08-21T03:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725514</loc>
  <lastmod>2026-08-21T03:34:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルベクトル自己回帰による予測・因果・インパルス応答の統合的解析（Forecasting, Causality, and Impulse Response with Neural Vector Autoregressions）</news:title>
   <news:publication_date>2026-08-21T03:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725512</loc>
  <lastmod>2026-08-21T02:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学組成のベイズ最適化とRFe12型磁石への応用（Bayesian optimization of chemical composition: a comprehensive framework and its application to RFe12-type magnet compounds）</news:title>
   <news:publication_date>2026-08-21T02:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725510</loc>
  <lastmod>2026-08-21T02:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配のみのラインサーチ（Gradient-only line searches: An Alternative to Probabilistic Line Searches）</news:title>
   <news:publication_date>2026-08-21T02:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725508</loc>
  <lastmod>2026-08-21T02:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル確率的予測による相互行動の解釈可能なモデル（Multi-modal Probabilistic Prediction of Interactive Behavior via an Interpretable Model）</news:title>
   <news:publication_date>2026-08-21T02:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725506</loc>
  <lastmod>2026-08-21T02:42:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙の正則化による高次元線形回帰（High-Dimensional Linear Regression via Implicit Regularization）</news:title>
   <news:publication_date>2026-08-21T02:42:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725504</loc>
  <lastmod>2026-08-21T02:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層フィクティシャス・プレイによる確率微分ゲームの解法（Deep Fictitious Play for Stochastic Differential Games）</news:title>
   <news:publication_date>2026-08-21T02:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725502</loc>
  <lastmod>2026-08-21T02:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス分解によるマクロアクション強化学習（Macro Action Reinforcement Learning with Sequence Disentanglement using Variational Autoencoder）</news:title>
   <news:publication_date>2026-08-21T02:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725500</loc>
  <lastmod>2026-08-21T02:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階目標抽象による深層階層強化学習推薦（Deep Hierarchical Reinforcement Learning Based Recommendations via Multi-goals Abstraction）</news:title>
   <news:publication_date>2026-08-21T02:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725498</loc>
  <lastmod>2026-08-21T01:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D顔再構成を2D画像で補助する学習法（3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild）</news:title>
   <news:publication_date>2026-08-21T01:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725496</loc>
  <lastmod>2026-08-21T01:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さなミニライゾトロンデータセットを乗り越える転移学習（Overcoming Small Minirhizotron Datasets Using Transfer Learning）</news:title>
   <news:publication_date>2026-08-21T01:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725494</loc>
  <lastmod>2026-08-21T01:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二分空間分割フォレスト（Binary Space Partitioning Forests）</news:title>
   <news:publication_date>2026-08-21T01:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725492</loc>
  <lastmod>2026-08-21T01:49:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Binary Space Partitioning-Tree Process（The Binary Space Partitioning-Tree Process）</news:title>
   <news:publication_date>2026-08-21T01:49:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725490</loc>
  <lastmod>2026-08-21T01:49:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習で解釈可能な決定木を学ぶ最適化手法（Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-21T01:49:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725488</loc>
  <lastmod>2026-08-21T01:49:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MNMFを用いた教師なし音声強調とMVDRビームフォーミング（Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming）</news:title>
   <news:publication_date>2026-08-21T01:49:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725486</loc>
  <lastmod>2026-08-21T01:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダル画像の教師なし変形登録を離散表現で解く（Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations）</news:title>
   <news:publication_date>2026-08-21T01:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725484</loc>
  <lastmod>2026-08-21T00:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光コヒーレンストモグラフィ（OCT）画像のスペックル低減のためのResNetベース汎用手法 (A RESNET-BASED UNIVERSAL METHOD FOR SPECKLE REDUCTION IN OPTICAL COHERENCE TOMOGRAPHY IMAGES)</news:title>
   <news:publication_date>2026-08-21T00:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725482</loc>
  <lastmod>2026-08-21T00:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>けいれんと非けいれんの分類に対する新規IndRNNアプローチ (A Novel Independent RNN Approach to Classification of Seizures against Non-seizures)</news:title>
   <news:publication_date>2026-08-21T00:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725480</loc>
  <lastmod>2026-08-21T00:55:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層多天体分光観測がLSSTのダークエネルギー研究を強化する（Deep Multi-object Spectroscopy to Enhance Dark Energy Science from LSST）</news:title>
   <news:publication_date>2026-08-21T00:55:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725478</loc>
  <lastmod>2026-08-21T00:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広域多天体分光観測がLSSTの暗黒エネルギー研究にもたらすもの（Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST）</news:title>
   <news:publication_date>2026-08-21T00:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725476</loc>
  <lastmod>2026-08-21T00:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一天体の撮像と分光がLSSTの暗黒エネルギー研究を強化する（Single-object Imaging and Spectroscopy to Enhance Dark Energy Science from LSST）</news:title>
   <news:publication_date>2026-08-21T00:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725474</loc>
  <lastmod>2026-08-21T00:54:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散電子医療記録を用いた患者クラスタリングはフェデレーテッド機械学習の効率を改善する（Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records）</news:title>
   <news:publication_date>2026-08-21T00:54:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725472</loc>
  <lastmod>2026-08-21T00:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境における加重ワンショット・リッジ回帰の実務的意義（WONDER: Weighted one-shot distributed ridge regression in high dimensions）</news:title>
   <news:publication_date>2026-08-21T00:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725470</loc>
  <lastmod>2026-08-21T00:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQNに基づくモデル内探索による効率的学習（DQN with Model-Based Exploration: Efficient Learning on Environments with Sparse Rewards）</news:title>
   <news:publication_date>2026-08-21T00:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725468</loc>
  <lastmod>2026-08-21T00:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成対抗学習による最適な構造化CNN剪定（Towards Optimal Structured CNN Pruning via Generative Adversarial Learning）</news:title>
   <news:publication_date>2026-08-21T00:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725466</loc>
  <lastmod>2026-08-21T00:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルデータ向け分離辞書の混合学習（Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms）</news:title>
   <news:publication_date>2026-08-21T00:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725464</loc>
  <lastmod>2026-08-21T00:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HARDIの高速かつ高精度な再構成を実現する1Dエンコーダ・デコーダ畳み込みネットワーク（FAST AND ACCURATE RECONSTRUCTION OF HARDI USING A 1D ENCODER-DECODER CONVOLUTIONAL NETWORK）</news:title>
   <news:publication_date>2026-08-21T00:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725462</loc>
  <lastmod>2026-08-21T00:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワルファリン臨床用量アルゴリズムの適用範囲判定（A Computer-Aided System for Determining the Application Range of a Warfarin Clinical Dosing Algorithm Using Support Vector Machines with a Polynomial Kernel Function）</news:title>
   <news:publication_date>2026-08-21T00:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725460</loc>
  <lastmod>2026-08-20T23:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の生物医学データベースからアソシエーションルールとオントロジーを用いてメタデータ推奨を生成する方法（Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases）</news:title>
   <news:publication_date>2026-08-20T23:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725458</loc>
  <lastmod>2026-08-20T23:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ貼付ステッカーによる物理的攻撃（Adversarial camera stickers: A physical camera-based attack on deep learning systems）</news:title>
   <news:publication_date>2026-08-20T23:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725456</loc>
  <lastmod>2026-08-20T23:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間でU-Netを模倣する自己符号化器による骨盤骨セグメンテーション向上（Imitating U-Net Enhanced Autoencoders in Latent Space for Improved Pelvic Bone Segmentation in MRI）</news:title>
   <news:publication_date>2026-08-20T23:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725454</loc>
  <lastmod>2026-08-20T23:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙論と初期宇宙（Cosmology and the Early Universe）</news:title>
   <news:publication_date>2026-08-20T23:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725452</loc>
  <lastmod>2026-08-20T23:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散オフポリシーActor‑Criticと方策コンセンサス（Distributed off-Policy Actor-Critic Reinforcement Learning with Policy Consensus）</news:title>
   <news:publication_date>2026-08-20T23:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725450</loc>
  <lastmod>2026-08-20T23:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形フィルタリング総覧（The Hitchhiker’s Guide to Nonlinear Filtering）</news:title>
   <news:publication_date>2026-08-20T23:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725448</loc>
  <lastmod>2026-08-20T23:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間領域で学習可能な時系列整列手法：Trainable Time Warping（Trainable Time Warping: Aligning Time-Series in the Continuous-Time Domain）</news:title>
   <news:publication_date>2026-08-20T23:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725446</loc>
  <lastmod>2026-08-20T23:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット指示の効率的自然言語理解のためのコンパクト表現の推定 (Inferring Compact Representations for Efficient Natural Language Understanding of Robot Instructions)</news:title>
   <news:publication_date>2026-08-20T23:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725444</loc>
  <lastmod>2026-08-20T23:06:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ULMFitとバックトランスレーションによる少量データのテキスト分類（Low Resource Text Classification with ULMFit and Backtranslation）</news:title>
   <news:publication_date>2026-08-20T23:06:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725442</loc>
  <lastmod>2026-08-20T22:15:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ系列MRIを用いた脳腫瘍検出と分類のDeep Radiomics（Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI）</news:title>
   <news:publication_date>2026-08-20T22:15:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725440</loc>
  <lastmod>2026-08-20T22:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン敵対学習が変える現場導入の常識（Multi-Domain Adversarial Learning）</news:title>
   <news:publication_date>2026-08-20T22:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725438</loc>
  <lastmod>2026-08-20T22:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化付き混合線形回帰モデルにおけるパラメータ推定の収束性（Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models）</news:title>
   <news:publication_date>2026-08-20T22:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725436</loc>
  <lastmod>2026-08-20T22:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Top-1誤差に注目した較正済み不確実性推定（Calibrated Top-1 Uncertainty estimates for classification by score based models）</news:title>
   <news:publication_date>2026-08-20T22:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725434</loc>
  <lastmod>2026-08-20T22:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状理解のためのSkelNetOnチャレンジ（SkelNetOn 2019: Dataset and Challenge on Deep Learning for Geometric Shape Understanding）</news:title>
   <news:publication_date>2026-08-20T22:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725432</loc>
  <lastmod>2026-08-20T22:13:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞同定のための確率的アトラス（A probabilistic atlas for cell identification）</news:title>
   <news:publication_date>2026-08-20T22:13:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725430</loc>
  <lastmod>2026-08-20T22:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高閾値活性化を用いた深層ネットワークの最下層復元（Recovering the Lowest Layer of Deep Networks with High Threshold Activations）</news:title>
   <news:publication_date>2026-08-20T22:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725428</loc>
  <lastmod>2026-08-20T21:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクロステーショナリ過程のネットワークにおける正確なトポロジー学習（Exact Topology Learning in a Network of Cyclostationary Processes）</news:title>
   <news:publication_date>2026-08-20T21:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725426</loc>
  <lastmod>2026-08-20T21:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Penobscotデータセット：地震データで機械学習を育てる（Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation）</news:title>
   <news:publication_date>2026-08-20T21:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725424</loc>
  <lastmod>2026-08-20T21:20:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システム全体を視野に入れた動的評価フレームワーク（A simulation based dynamic evaluation framework for system-wide algorithmic fairness）</news:title>
   <news:publication_date>2026-08-20T21:20:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725422</loc>
  <lastmod>2026-08-20T21:19:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種混合マルチタスク学習のためのマルチネットワーク自動構築に向けて（Towards automatic construction of multi-network models for heterogeneous multi-task learning）</news:title>
   <news:publication_date>2026-08-20T21:19:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725420</loc>
  <lastmod>2026-08-20T21:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエーサーのマイクロレンズ光度曲線解析に深層学習を用いる研究（Quasar microlensing light curve analysis using deep machine learning）</news:title>
   <news:publication_date>2026-08-20T21:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725418</loc>
  <lastmod>2026-08-20T21:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のマルチラベル分類API比較とセマンティック評価の重要性（Comparison of State-of-the-Art Deep Learning APIs for Image Multi-Label Classification using Semantic Metrics）</news:title>
   <news:publication_date>2026-08-20T21:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725416</loc>
  <lastmod>2026-08-20T21:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparse2Denseによる単眼SLAMの密な再構築（Sparse2Dense: From direct sparse odometry to dense 3D reconstruction）</news:title>
   <news:publication_date>2026-08-20T21:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725414</loc>
  <lastmod>2026-08-20T20:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAスペクトロスコピー調査が示す分子ガスの宇宙進化（The ALMA Spectroscopic Survey in the Hubble Ultra Deep Field: Evolution of the molecular gas in CO-selected galaxies）</news:title>
   <news:publication_date>2026-08-20T20:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725412</loc>
  <lastmod>2026-08-20T20:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光調査が示した銀河ガスの実像（The ALMA Spectroscopic Survey in the HUDF: Nature and physical properties of gas-mass selected galaxies using MUSE spectroscopy）</news:title>
   <news:publication_date>2026-08-20T20:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725410</loc>
  <lastmod>2026-08-20T20:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光サーベイ：銀河のCO輝度関数と宇宙史を通じた分子ガス量の変遷（THE ALMA SPECTROSCOPIC SURVEY IN THE HUDF: CO LUMINOSITY FUNCTIONS AND THE MOLECULAR GAS CONTENT OF GALAXIES THROUGH COSMIC HISTORY）</news:title>
   <news:publication_date>2026-08-20T20:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725408</loc>
  <lastmod>2026-08-20T20:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを「害さない」補間の理論 — 高次元線形回帰における無害な補間（Harmless interpolation of noisy data in regression）</news:title>
   <news:publication_date>2026-08-20T20:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725406</loc>
  <lastmod>2026-08-20T20:15:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光調査：銀河の分子ガス量とモデルとの乖離（The ALMA Spectroscopic Survey in the HUDF: the molecular gas content of galaxies and tensions with IllustrisTNG and the Santa Cruz SAM）</news:title>
   <news:publication_date>2026-08-20T20:15:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725404</loc>
  <lastmod>2026-08-20T20:15:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光観測：CO輝線と3mm連続体源（The ALMA Spectroscopic Survey in the HUDF: CO emission lines and 3 mm continuum sources）</news:title>
   <news:publication_date>2026-08-20T20:15:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725402</loc>
  <lastmod>2026-08-20T20:15:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転するブラックホールによる潮汐破壊の影響（Tidal disruptions by rotating black holes: effects of spin and impact parameter）</news:title>
   <news:publication_date>2026-08-20T20:15:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725400</loc>
  <lastmod>2026-08-20T19:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動履歴探索による確率的線形バンディット（Perturbed-History Exploration in Stochastic Linear Bandits）</news:title>
   <news:publication_date>2026-08-20T19:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725398</loc>
  <lastmod>2026-08-20T19:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衝撃を受けたHMXにおけるメソスケールのエネルギー局在化のモデル化（Modeling meso-scale energy localization in shocked HMX, Part II: training machine-learned surrogate models for void shape and void-void interaction effects）</news:title>
   <news:publication_date>2026-08-20T19:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725396</loc>
  <lastmod>2026-08-20T19:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形ガウス近似メッセージ伝播の近似手法（ON APPROXIMATE NONLINEAR GAUSSIAN MESSAGE PASSING ON FACTOR GRAPHS）</news:title>
   <news:publication_date>2026-08-20T19:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725394</loc>
  <lastmod>2026-08-20T19:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>孤立波（ローグウェーブ）事象の持続時間解析（Lifetimes of rogue wave events in direct numerical simulations of deep-water irregular sea waves）</news:title>
   <news:publication_date>2026-08-20T19:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725392</loc>
  <lastmod>2026-08-20T19:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的システム同定の有限サンプル解析（Finite Sample Analysis of Stochastic System Identification）</news:title>
   <news:publication_date>2026-08-20T19:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725390</loc>
  <lastmod>2026-08-20T19:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度カメラとサンプルエントロピーによる歩行パターン解析（Exploratory studies of human gait changes using depth cameras and sample entropy）</news:title>
   <news:publication_date>2026-08-20T19:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725388</loc>
  <lastmod>2026-08-20T19:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習におけるタスク類似性学習の原理的アプローチ（A Principled Approach for Learning Task Similarity in Multitask Learning）</news:title>
   <news:publication_date>2026-08-20T19:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725386</loc>
  <lastmod>2026-08-20T18:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走査プローブの状態認識を自動化するニューラルネットワーク群（Scanning Probe State Recognition With Multi-Class Neural Network Ensembles）</news:title>
   <news:publication_date>2026-08-20T18:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725384</loc>
  <lastmod>2026-08-20T18:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子グラフの階層的潜在表現：グループを明示するティア方式（Tiered Latent Representations and Latent Spaces for Molecular Graphs）</news:title>
   <news:publication_date>2026-08-20T18:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725382</loc>
  <lastmod>2026-08-20T18:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼動画からの衝突までの時間予測（Forecasting Time-to-Collision from Monocular Video: Feasibility, Dataset, and Challenges）</news:title>
   <news:publication_date>2026-08-20T18:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725380</loc>
  <lastmod>2026-08-20T18:27:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stripe 82深層画像による銀河のバルジ・ディスク分解カタログ（Bulge plus disc and Sérsic decomposition catalogues for 16,908 galaxies in the SDSS Stripe 82 co-adds）</news:title>
   <news:publication_date>2026-08-20T18:27:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725378</loc>
  <lastmod>2026-08-20T18:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別の快適温度を少ない問合せで学ぶ（Learning Personalized Thermal Preferences via Bayesian Active Learning with Unimodality Constraints）</news:title>
   <news:publication_date>2026-08-20T18:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725376</loc>
  <lastmod>2026-08-20T18:27:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算制約下のエッジサービス配置と需要推定（Budget-constrained Edge Service Provisioning with Demand Estimation via Bandit Learning）</news:title>
   <news:publication_date>2026-08-20T18:27:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725374</loc>
  <lastmod>2026-08-20T18:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>狭い隙間をニューラルネットワークで飛行させる—エンドツーエンド計画と制御のアプローチ（Flying through a narrow gap using neural network: an end-to-end planning and control approach）</news:title>
   <news:publication_date>2026-08-20T18:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725372</loc>
  <lastmod>2026-08-20T17:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期に迫る――LAGERが示したz≈7のライマンα銀河の意味（LYMAN ALPHA GALAXIES IN THE EPOCH OF REIONIZATION）</news:title>
   <news:publication_date>2026-08-20T17:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725370</loc>
  <lastmod>2026-08-20T17:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等変性を持つエンティティ関係ネットワーク（Equivariant Entity-Relationship Networks）</news:title>
   <news:publication_date>2026-08-20T17:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725368</loc>
  <lastmod>2026-08-20T17:34:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別処方型サポートベクターマシンによる再入院抑止（Prescriptive Cluster-Dependent Support Vector Machines with an Application to Reducing Hospital Readmissions）</news:title>
   <news:publication_date>2026-08-20T17:34:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725366</loc>
  <lastmod>2026-08-20T17:33:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在単体位相モデル：多視点クラスタリングと不確実性の可視化（Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification）</news:title>
   <news:publication_date>2026-08-20T17:33:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725364</loc>
  <lastmod>2026-08-20T17:33:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データが乏しくても深層学習を使うための生成モデル（Generative Models For Deep Learning with Very Scarce Data）</news:title>
   <news:publication_date>2026-08-20T17:33:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725362</loc>
  <lastmod>2026-08-20T17:33:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内廊下環境における単眼カメラを用いたUAV位置推定（Localization of Unmanned Aerial Vehicles in Corridor Environments using Deep Learning）</news:title>
   <news:publication_date>2026-08-20T17:33:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725360</loc>
  <lastmod>2026-08-20T17:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブグラフネットワークによる構造特徴空間の拡張（Subgraph Networks with Application to Structural Feature Space Expansion）</news:title>
   <news:publication_date>2026-08-20T17:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725358</loc>
  <lastmod>2026-08-20T16:41:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ココエルシビティ、平滑性とバイアスが変える分散低減確率的勾配法（Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods）</news:title>
   <news:publication_date>2026-08-20T16:41:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725356</loc>
  <lastmod>2026-08-20T16:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非共有結合に対する量子機械学習補正が密度汎関数計算を変える（Non-covalent quantum machine learning corrections to density functionals）</news:title>
   <news:publication_date>2026-08-20T16:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725354</loc>
  <lastmod>2026-08-20T16:40:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HYDRAによる応力最小化型ハイパーボリック埋め込み（HYDRA: A METHOD FOR STRAIN-MINIMIZING HYPERBOLIC EMBEDDING OF NETWORK- AND DISTANCE-BASED DATA）</news:title>
   <news:publication_date>2026-08-20T16:40:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725352</loc>
  <lastmod>2026-08-20T16:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的時系列解析による薬物応答モデル化（Multi-Task Time Series Analysis applied to Drug Response Modelling）</news:title>
   <news:publication_date>2026-08-20T16:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725350</loc>
  <lastmod>2026-08-20T16:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>斜め落下する液滴の深い液槽への衝突（Oblique droplet impact onto a deep liquid pool）</news:title>
   <news:publication_date>2026-08-20T16:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725348</loc>
  <lastmod>2026-08-20T16:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市販サラダの微生物汚染評価のための統一スペクトル解析ワークフロー（A unified spectra analysis workflow for the assessment of microbial contamination of ready-to-eat green salads）</news:title>
   <news:publication_date>2026-08-20T16:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725346</loc>
  <lastmod>2026-08-20T15:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期予測とマルチカメラ融合によるセマンティックグリッド（Short-Term Prediction and Multi-Camera Fusion on Semantic Grids）</news:title>
   <news:publication_date>2026-08-20T15:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725344</loc>
  <lastmod>2026-08-20T15:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られたデータで機械的聴覚を改善する方法（Improving Machine Hearing on Limited Data Sets）</news:title>
   <news:publication_date>2026-08-20T15:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725342</loc>
  <lastmod>2026-08-20T15:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話応答選択における階層的情報学習（Learning Multi-Level Information for Dialogue Response Selection）</news:title>
   <news:publication_date>2026-08-20T15:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725340</loc>
  <lastmod>2026-08-20T15:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みと規則を反復学習する知識グラフ推論（Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning）</news:title>
   <news:publication_date>2026-08-20T15:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725338</loc>
  <lastmod>2026-08-20T15:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>後期M型矮星の均質サンプル化が示す地平（A homogeneous sample of 34 000 M7−M9.5 dwarfs brighter than J = 17.5）</news:title>
   <news:publication_date>2026-08-20T15:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725336</loc>
  <lastmod>2026-08-20T15:47:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴でMCTSをバイアスする一般ゲームへの適用（Biasing MCTS with Features for General Games）</news:title>
   <news:publication_date>2026-08-20T15:47:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725334</loc>
  <lastmod>2026-08-20T15:46:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-20T15:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725332</loc>
  <lastmod>2026-08-20T14:54:52Z</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>2026-08-20T14:54:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725330</loc>
  <lastmod>2026-08-20T14:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ単位の最適輸送損失による3D形状認識の高速化と精度改善（Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition）</news:title>
   <news:publication_date>2026-08-20T14:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725328</loc>
  <lastmod>2026-08-20T14:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PPGnetによるデバイス非依存心拍数推定（PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram）</news:title>
   <news:publication_date>2026-08-20T14:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725326</loc>
  <lastmod>2026-08-20T14:53:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報の「写し」と「変換」を分解する（Decomposing information into copying versus transformation）</news:title>
   <news:publication_date>2026-08-20T14:53:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725324</loc>
  <lastmod>2026-08-20T14:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的グラフにおけるノード埋め込み（Node Embedding over Temporal Graphs）</news:title>
   <news:publication_date>2026-08-20T14:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725322</loc>
  <lastmod>2026-08-20T14:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>風力タービンの稼働状態分類モデルの移植性（Transferability of Operational Status Classification Models Among Different Wind Turbine Types）</news:title>
   <news:publication_date>2026-08-20T14:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725320</loc>
  <lastmod>2026-08-20T14:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Q-Learningにおける発散の特徴づけ（Towards Characterizing Divergence in Deep Q-Learning）</news:title>
   <news:publication_date>2026-08-20T14:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725318</loc>
  <lastmod>2026-08-20T14:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化多層テンソル学習と画像解析への応用（Individualized Multilayer Tensor Learning with An Application in Imaging Analysis）</news:title>
   <news:publication_date>2026-08-20T14:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725316</loc>
  <lastmod>2026-08-20T14:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNベース音源強調のための完全再構成フィルタバンクのデータ駆動設計 (DATA-DRIVEN DESIGN OF PERFECT RECONSTRUCTION FILTERBANK FOR DNN-BASED SOUND SOURCE ENHANCEMENT)</news:title>
   <news:publication_date>2026-08-20T14:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725314</loc>
  <lastmod>2026-08-20T14:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床データにおける発作検出と分類の畳み込みニューラルネットワーク（Convolutional neural network for detection and classification of seizures in clinical data）</news:title>
   <news:publication_date>2026-08-20T14:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725312</loc>
  <lastmod>2026-08-20T14:00:00Z</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>2026-08-20T14:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725310</loc>
  <lastmod>2026-08-20T13:59:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳接続性とCNNによる統合的分類アプローチ（Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-20T13:59:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725308</loc>
  <lastmod>2026-08-20T13:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OverSketched Newtonによるサーバレス最適化の実務的意義（OverSketched Newton: Fast Convex Optimization for Serverless Systems）</news:title>
   <news:publication_date>2026-08-20T13:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725306</loc>
  <lastmod>2026-08-20T13:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像時系列の分離表現学習（Learning Disentangled Representations of Satellite Image Time Series）</news:title>
   <news:publication_date>2026-08-20T13:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725304</loc>
  <lastmod>2026-08-20T13:07:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一入力出力層スパイキング分類器と時変重みモデルの効率化（Efficient single input-output layer spiking neural classifier with time-varying weight model）</news:title>
   <news:publication_date>2026-08-20T13:07:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725302</loc>
  <lastmod>2026-08-20T13:07:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ジオメトリ認識に基づく弱教師あり学習による3D人体姿勢推定（Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725300</loc>
  <lastmod>2026-08-20T13:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-20T13:06:47Z</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>運転シーンにおける時間的ダイナミクス情報の価値（Value of Temporal Dynamics Information in Driving Scene Segmentation）</news:title>
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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>
   </news:publication>
   <news:title>半正則三角メッシュ上の畳み込みニューラルネットワークと脳画像への応用（Convolutional Neural Network on Semi-Regular Triangulated Meshes and its Application to Brain Image Data）</news:title>
   <news:publication_date>2026-08-20T13:05:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725294</loc>
  <lastmod>2026-08-20T13:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-20T13:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725292</loc>
  <lastmod>2026-08-20T13:05:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ディリクレ過程に対する正確なスライスサンプラー（Exact slice sampler for Hierarchical Dirichlet Processes）</news:title>
   <news:publication_date>2026-08-20T13:05:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725289</loc>
  <lastmod>2026-08-20T12:13:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的粒子群最適化で進化させる深層ニューラルネット（Evolving Deep Neural Networks by Multi-objective Particle Swarm Optimization for Image Classification）</news:title>
   <news:publication_date>2026-08-20T12:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725287</loc>
  <lastmod>2026-08-20T12:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dual Residual Networksによる画像復元の新展開（Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration）</news:title>
   <news:publication_date>2026-08-20T12:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725285</loc>
  <lastmod>2026-08-20T12:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アフィン変換と非パラメトリックを同時に扱う3D画像登録のネットワーク（Networks for Joint Affine and Non-parametric Image Registration）</news:title>
   <news:publication_date>2026-08-20T12:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725283</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>入力点を中心に最大のℓp球をはめる方法（Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes）</news:title>
   <news:publication_date>2026-08-20T12:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725281</loc>
  <lastmod>2026-08-20T12:11:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットの解釈をフリップポイントで考える（Interpreting Neural Networks Using Flip Points）</news:title>
   <news:publication_date>2026-08-20T12:11:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725279</loc>
  <lastmod>2026-08-20T12:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全性重視のエンドツーエンド強化学習—制御バリア関数を用いた安全保証（End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks）</news:title>
   <news:publication_date>2026-08-20T12:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725277</loc>
  <lastmod>2026-08-20T12:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる機械学習と自動化をつなぐ枠組み（A Unified Analytical Framework for Trustable Machine Learning and Automation Running with Blockchain）</news:title>
   <news:publication_date>2026-08-20T12:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725275</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>民族歌のモチーフの分散ベクトル表現（Distributed Vector Representations of Folksong Motifs）</news:title>
   <news:publication_date>2026-08-20T11:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725273</loc>
  <lastmod>2026-08-20T11:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GBMを加速する考え方と実装の要点（Accelerating Gradient Boosting Machines）</news:title>
   <news:publication_date>2026-08-20T11:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725271</loc>
  <lastmod>2026-08-20T11:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Byzantine耐性分散線形回帰（Byzantine Fault Tolerant Distributed Linear Regression）</news:title>
   <news:publication_date>2026-08-20T11:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725269</loc>
  <lastmod>2026-08-20T11:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーション品質評価の堅牢化（Robust Image Segmentation Quality Assessment）</news:title>
   <news:publication_date>2026-08-20T11:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725267</loc>
  <lastmod>2026-08-20T11:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きバッチ方策学習（Batch Policy Learning under Constraints）</news:title>
   <news:publication_date>2026-08-20T11:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725265</loc>
  <lastmod>2026-08-20T11:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直接知覚におけるアフォーダンス学習が自動運転を変える（Affordance Learning In Direct Perception for Autonomous Driving）</news:title>
   <news:publication_date>2026-08-20T11:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725263</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>ノイジー加速べき乗法による固有値問題の効率化（Noisy Accelerated Power Method for Eigenproblems with Applications）</news:title>
   <news:publication_date>2026-08-20T11:17:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725261</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>2026-08-20T10:25:36Z</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>量子オートエンコーダによる損失なし量子データ圧縮の実現（Realization of a quantum autoencoder for lossless compression of quantum data）</news:title>
   <news:publication_date>2026-08-20T10:25:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725257</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>局所経験を活かしたグローバル動作計画（Using Local Experiences for Global Motion Planning）</news:title>
   <news:publication_date>2026-08-20T10:25:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725255</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド空間における効率的な内積近似（Efficient Inner Product Approximation in Hybrid Spaces）</news:title>
   <news:publication_date>2026-08-20T10:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725253</loc>
  <lastmod>2026-08-20T10:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Polyakの学習率を用いた確率的勾配降下法（Stochastic Gradient Descent with Polyak’s Learning Rate）</news:title>
   <news:publication_date>2026-08-20T10:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725251</loc>
  <lastmod>2026-08-20T10:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子回路のパラメータ化とキュービット品質の時間変動への対処（Addressing Temporal Variations in Qubit Quality Metrics for Parameterized Quantum Circuits）</news:title>
   <news:publication_date>2026-08-20T10:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725249</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>エネルギー基底モデルによる暗黙的生成とモデリング（Implicit Generation and Modeling with Energy-Based Models）</news:title>
   <news:publication_date>2026-08-20T10:23:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725247</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>写真から自在に鉛筆画を作る技術の要点（Im2Pencil: Controllable Pencil Illustration from Photographs）</news:title>
   <news:publication_date>2026-08-20T09:32:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725245</loc>
  <lastmod>2026-08-20T09:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン継続学習のための勾配ベースサンプル選択（Gradient based sample selection for online continual learning）</news:title>
   <news:publication_date>2026-08-20T09:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725243</loc>
  <lastmod>2026-08-20T09:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TATi—熱力学解析ツールキット（TATi-Thermodynamic Analytics ToolkIt: TensorFlow-based software for posterior sampling in machine learning applications）</news:title>
   <news:publication_date>2026-08-20T09:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725241</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>磁気選択的増強で学習が速い分子スピンバルブのシナプス（Fast learning synapses with molecular spin valves via selective magnetic potentiation）</news:title>
   <news:publication_date>2026-08-20T09:30:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725239</loc>
  <lastmod>2026-08-20T09:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的部分多様体に対する近似情報検定（Approximate Information Tests on Statistical Submanifolds）</news:title>
   <news:publication_date>2026-08-20T09:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725237</loc>
  <lastmod>2026-08-20T09:30:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Column2Vecによるデータベーススキーマの分散表現（Column2Vec: Structural Understanding via Distributed Representations of Database Schemas）</news:title>
   <news:publication_date>2026-08-20T09:30:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725235</loc>
  <lastmod>2026-08-20T09:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的最適化におけるより良いモデルの重要性（The importance of better models in stochastic optimization）</news:title>
   <news:publication_date>2026-08-20T09:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725233</loc>
  <lastmod>2026-08-20T08:38:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン食事調査における省略食品を促すレコメンダーの検証（Validation of a recommender system for prompting omitted foods in online dietary assessment surveys）</news:title>
   <news:publication_date>2026-08-20T08:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725231</loc>
  <lastmod>2026-08-20T08:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的運転に対する単一ステップオプション（Single-step Options for Adversary Driving）</news:title>
   <news:publication_date>2026-08-20T08:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725229</loc>
  <lastmod>2026-08-20T08:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所特徴のバッグモデルでCNNを近似するとImageNetで驚くほど高精度である（Approximating CNNs with Bag-of-Local-Features Models Works Surprisingly Well on ImageNet）</news:title>
   <news:publication_date>2026-08-20T08:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725227</loc>
  <lastmod>2026-08-20T08:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DC-SPP-YOLOによる物体検出の改良（DC-SPP-YOLO: Dense Connection and Spatial Pyramid Pooling Based YOLO for Object Detection）</news:title>
   <news:publication_date>2026-08-20T08:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725225</loc>
  <lastmod>2026-08-20T08:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wikipediaをグラフで扱うためのデータセット整備（A graph-structured dataset for Wikipedia research）</news:title>
   <news:publication_date>2026-08-20T08:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/725223</loc>
  <lastmod>2026-08-20T08:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <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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 <url>
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    <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>
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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: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>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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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>
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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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    <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>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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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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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:language>ja</news:language>
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   <news:title>電子カルテの階層表現で臨床予測を強化するアプローチ（Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction）</news:title>
   <news:publication_date>2026-08-20T04:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725151</loc>
  <lastmod>2026-08-20T03:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チェックすべき文の自動抽出を強化するニューラルランキング（Neural Check-Worthiness Ranking with Weak Supervision）</news:title>
   <news:publication_date>2026-08-20T03:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725149</loc>
  <lastmod>2026-08-20T03:14:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続する音楽トラックのスキップ予測を行うMulti-RNNアプローチ（Modelling Sequential Music Track Skips using a Multi-RNN Approach）</news:title>
   <news:publication_date>2026-08-20T03:14:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725147</loc>
  <lastmod>2026-08-20T03:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ誤差のモデル化と堅牢なグラフ信号処理への道（Modelling Graph Errors: Towards Robust Graph Signal Processing）</news:title>
   <news:publication_date>2026-08-20T03:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725145</loc>
  <lastmod>2026-08-20T03:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データサイエンスが技術的痕跡探索にもたらす可能性（The Promise of Data Science for the Technosignatures Field）</news:title>
   <news:publication_date>2026-08-20T03:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725143</loc>
  <lastmod>2026-08-20T03:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きクエリグラフと重み付き集合に対する適応的多数問題 (Adaptive Majority Problems for Restricted Query Graphs and for Weighted Sets)</news:title>
   <news:publication_date>2026-08-20T03:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725141</loc>
  <lastmod>2026-08-20T03:13:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偶数サイズカーネルと対称パディングによる畳み込みの改善（Convolution with even-sized kernels and symmetric padding）</news:title>
   <news:publication_date>2026-08-20T03:13:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725139</loc>
  <lastmod>2026-08-20T03:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーツベースによる形態学的演算の近似（Part-based approximations for morphological operators using asymmetric auto-encoders）</news:title>
   <news:publication_date>2026-08-20T03:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725137</loc>
  <lastmod>2026-08-20T02:21:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習でモデルを自動拡張し圧縮する仕組み（Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML）</news:title>
   <news:publication_date>2026-08-20T02:21:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725135</loc>
  <lastmod>2026-08-20T02:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による動作生成の現状と意味（Machine Learning for Data-Driven Movement Generation: a Review of the State of the Art）</news:title>
   <news:publication_date>2026-08-20T02:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725133</loc>
  <lastmod>2026-08-20T02:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子特性予測の不確実性定量化（Uncertainty quantification of molecular property prediction with Bayesian neural networks）</news:title>
   <news:publication_date>2026-08-20T02:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725131</loc>
  <lastmod>2026-08-20T02:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的堅牢推論によるロボット認知の強化（GRIP: Generative Robust Inference and Perception for Semantic Robot Manipulation in Adversarial Environments）</news:title>
   <news:publication_date>2026-08-20T02:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725129</loc>
  <lastmod>2026-08-20T02:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Video Object Segmentationを使った視覚サーボと深度推定（Video Object Segmentation-based Visual Servo Control and Object Depth Estimation on a Mobile Robot）</news:title>
   <news:publication_date>2026-08-20T02:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725127</loc>
  <lastmod>2026-08-20T02:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変な最適測定角を伴う量子相関領域の検出可能性（On the possibility to detect quantum correlation regions with the variable optimal measurement angle）</news:title>
   <news:publication_date>2026-08-20T02:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725125</loc>
  <lastmod>2026-08-20T02:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データにおける多ラベル特徴選択の分散化（Distributed Maximization of Submodular plus Diversity Functions for Multi-label Feature Selection on Huge Datasets）</news:title>
   <news:publication_date>2026-08-20T02:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725123</loc>
  <lastmod>2026-08-20T01:27:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的レバレッジスコアに基づくランダム特徴サンプリングの実装と理論保証（On Sampling Random Features From Empirical Leverage Scores: Implementation and Theoretical Guarantees）</news:title>
   <news:publication_date>2026-08-20T01:27:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725121</loc>
  <lastmod>2026-08-20T01:27:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep K-近傍法の堅牢性に関する考察（On the Robustness of Deep K-Nearest Neighbors）</news:title>
   <news:publication_date>2026-08-20T01:27:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725119</loc>
  <lastmod>2026-08-20T01:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布に基づくゲーム理論的解概念の学習枠組み（A Learning Framework for Distribution-Based Game-Theoretic Solution Concepts）</news:title>
   <news:publication_date>2026-08-20T01:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725117</loc>
  <lastmod>2026-08-20T01:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳がん検診における放射線科医の性能向上に寄与する深層ニューラルネットワーク（Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening）</news:title>
   <news:publication_date>2026-08-20T01:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725115</loc>
  <lastmod>2026-08-20T01:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下鉱山車両のビジョンのみを用いたリアルタイム高精度自己位置推定（LookUP: Vision-Only Real-Time Precise Underground Localisation for Autonomous Mining Vehicles）</news:title>
   <news:publication_date>2026-08-20T01:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725113</loc>
  <lastmod>2026-08-20T01:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非剛体3D形状検索におけるマルチビュー・メトリック学習（NON-RIGID 3D SHAPE RETRIEVAL BASED ON MULTI-VIEW METRIC LEARNING）</news:title>
   <news:publication_date>2026-08-20T01:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725111</loc>
  <lastmod>2026-08-20T01:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未来を予測して言語から解釈可能な計画を作る—Prospectionによるロボット制御の読み方 (Prospection: Interpretable Plans From Language By Predicting the Future)</news:title>
   <news:publication_date>2026-08-20T01:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725109</loc>
  <lastmod>2026-08-20T00:34:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意図分類とスロットラベリングの高速で正確な統合設計（Simple, Fast, Accurate Intent Classification and Slot Labeling for Goal-Oriented Dialogue Systems）</news:title>
   <news:publication_date>2026-08-20T00:34:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725107</loc>
  <lastmod>2026-08-20T00:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定ラベルと大量非ラベルで効くGANベースのスパム検出（GANs for Semi-Supervised Opinion Spam Detection）</news:title>
   <news:publication_date>2026-08-20T00:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725105</loc>
  <lastmod>2026-08-20T00:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンでのコーヒー葉害虫・病害の検出と分類（A smartphone application to detection and classification of coffee leaf miner and coffee leaf rust）</news:title>
   <news:publication_date>2026-08-20T00:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725103</loc>
  <lastmod>2026-08-20T00:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的コンテキスト変数による効率的オフポリシーメタ強化学習 (Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables)</news:title>
   <news:publication_date>2026-08-20T00:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725101</loc>
  <lastmod>2026-08-20T00:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型医用画像分割における全畳み込みニューラルネットワーク（Interactive segmentation of medical images through fully convolutional neural networks）</news:title>
   <news:publication_date>2026-08-20T00:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725099</loc>
  <lastmod>2026-08-20T00:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指示動画から学ぶタスク横断弱教師あり学習（Cross-task Weakly Supervised Learning from Instructional Videos）</news:title>
   <news:publication_date>2026-08-20T00:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725097</loc>
  <lastmod>2026-08-20T00:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子アニーリングによる極端クラスタリングへのアプローチ（A Quantum Annealing-Based Approach to Extreme Clustering）</news:title>
   <news:publication_date>2026-08-20T00:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725095</loc>
  <lastmod>2026-08-19T23:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応ハードスレッショルディングによる一貫したロバスト回帰（Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression）</news:title>
   <news:publication_date>2026-08-19T23:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725093</loc>
  <lastmod>2026-08-19T23:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い ugrizY 画像とDEEP2/3 分光観測によるフォトメトリック赤方偏移検証（Deep ugrizY Imaging and DEEP2/3 Spectroscopy: A Photometric Redshift Testbed for LSST and Public Release of Data from the DEEP3 Galaxy Redshift Survey）</news:title>
   <news:publication_date>2026-08-19T23:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725091</loc>
  <lastmod>2026-08-19T23:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マーケティング疲労下における逐次選択バンディット問題の動的学習（Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue）</news:title>
   <news:publication_date>2026-08-19T23:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725089</loc>
  <lastmod>2026-08-19T23:39:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度映像における動作認識の実践的手法（3D Human Action Analysis and Recognition through GLAC descriptor on 2D Motion and Static Posture Images）</news:title>
   <news:publication_date>2026-08-19T23:39:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725087</loc>
  <lastmod>2026-08-19T23:39:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍ボイドで見つかった赤い超拡散銀河とその距離測定（Discovery of a red ultra-diffuse galaxy in a nearby void based on its globular cluster luminosity function）</news:title>
   <news:publication_date>2026-08-19T23:39:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725085</loc>
  <lastmod>2026-08-19T23:39:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>James Webb Telescopeによる深宇宙撮像サーベイの最大化（Maximising the power of deep extragalactic imaging surveys with the James Webb Space Telescope）</news:title>
   <news:publication_date>2026-08-19T23:39:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725083</loc>
  <lastmod>2026-08-19T23:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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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 <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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <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>
    <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: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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 <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: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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 </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: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>
   </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: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>
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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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 </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>
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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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   <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:publication_date>2026-08-19T18:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-19T18:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-19T18:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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  <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>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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  <news: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>
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 <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>
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   <news:genres>Blog</news:genres>
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 <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>
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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>2026-08-19T17:13:03Z</news:publication_date>
   <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:publication_date>2026-08-19T17:12:50Z</news:publication_date>
   <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: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>
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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: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>
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 </url>
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  <loc>https://aibr.jp/archives/724981</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>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724979</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>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>
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   <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>
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   <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>
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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>
  </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>
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   <news:publication_date>2026-08-19T16:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </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>
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   <news:publication_date>2026-08-19T15:26:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/724967</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>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>
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 </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>
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   <news:genres>Blog</news:genres>
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 </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>
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   <news:genres>Blog</news:genres>
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 </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>
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   <news:genres>Blog</news:genres>
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 </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>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/724957</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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