<?xml version="1.0" encoding="UTF-8"?>
<!--generator='jetpack-15.8-a.7'-->
<!--Jetpack_Sitemap_Buffer_News_XMLWriter-->
<?xml-stylesheet type="text/xsl" href="//aibr.jp/news-sitemap.xsl"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.sitemaps.org/schemas/sitemap/0.9 http://www.sitemaps.org/schemas/sitemap/0.9/sitemap.xsd">
 <url>
  <loc>https://aibr.jp/archives/686020</loc>
  <lastmod>2026-05-03T07:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの普遍的エンコーダの提案（Towards a Universal Neural Network Encoder for Time Series）</news:title>
   <news:publication_date>2026-05-03T07:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686018</loc>
  <lastmod>2026-05-03T07:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EM-Softmaxが変える画像分類の精度向上（Ensemble Soft-Margin Softmax Loss for Image Classification）</news:title>
   <news:publication_date>2026-05-03T07:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686016</loc>
  <lastmod>2026-05-03T07:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド状データに対するラベリングの定式化（Labelling as an unsupervised learning problem）</news:title>
   <news:publication_date>2026-05-03T07:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686014</loc>
  <lastmod>2026-05-03T07:17:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非形式的数学記述を形式化するニューラル翻訳の第一歩（First Experiments with Neural Translation of Informal to Formal Mathematics）</news:title>
   <news:publication_date>2026-05-03T07:17:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686012</loc>
  <lastmod>2026-05-03T07:16:30Z</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連想分類器の分散化（Scaling associative classification for very large datasets）</news:title>
   <news:publication_date>2026-05-03T07:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686010</loc>
  <lastmod>2026-05-03T07:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失を考慮した近似推論によるベイズニューラルネットの実務的意義（Loss-Calibrated Approximate Inference in Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-05-03T07:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686008</loc>
  <lastmod>2026-05-03T07:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話を続けるチャットボットのための「Second Response Generation」研究（Improv Chat: Second Response Generation for Chatbot）</news:title>
   <news:publication_date>2026-05-03T07:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686006</loc>
  <lastmod>2026-05-03T06:25:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Freebase再構成から読み解く知識グラフの設計思想（OK Google, What Is Your Ontology?）</news:title>
   <news:publication_date>2026-05-03T06:25:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686004</loc>
  <lastmod>2026-05-03T06:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンドット手法による頑健な探索戦略の学習（Learning Robust Search Strategies Using a Bandit-Based Approach）</news:title>
   <news:publication_date>2026-05-03T06:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686002</loc>
  <lastmod>2026-05-03T06:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄化が非対称再帰型ニューラルネットワークに与える影響（Effect of dilution in asymmetric recurrent neural networks）</news:title>
   <news:publication_date>2026-05-03T06:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686000</loc>
  <lastmod>2026-05-03T06:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア開発における人的資本の可視化と指標化（Human Capital in Software Engineering: A Systematic Mapping of Reconceptualized Human Aspect Studies）</news:title>
   <news:publication_date>2026-05-03T06:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685998</loc>
  <lastmod>2026-05-03T06:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hybrid Adaptive Fuzzy Extreme Learning Machineの概説（Hybrid Adaptive Fuzzy Extreme Learning Machine for text classification）</news:title>
   <news:publication_date>2026-05-03T06:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685996</loc>
  <lastmod>2026-05-03T06:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔表情認識のための深層共分散記述子（Deep Covariance Descriptors for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-05-03T06:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685994</loc>
  <lastmod>2026-05-03T06:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンサンブル極限学習機によるテキスト分類（Text classification based on ensemble extreme learning machine）</news:title>
   <news:publication_date>2026-05-03T06:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685992</loc>
  <lastmod>2026-05-03T05:32:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン感受性と感情を考慮した単語埋め込み（Learning Domain-Sensitive and Sentiment-Aware Word Embeddings）</news:title>
   <news:publication_date>2026-05-03T05:32:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685990</loc>
  <lastmod>2026-05-03T05:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック損失関数の普遍性（On the Universality of the Logistic Loss Function）</news:title>
   <news:publication_date>2026-05-03T05:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685988</loc>
  <lastmod>2026-05-03T05:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論志向の読解評価：ParallelQA（Towards Inference-Oriented Reading Comprehension: ParallelQA）</news:title>
   <news:publication_date>2026-05-03T05:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685986</loc>
  <lastmod>2026-05-03T05:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイバ非線形性を含む幾何学的コンステレーションシェーピングの深層学習 (Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities)</news:title>
   <news:publication_date>2026-05-03T05:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685984</loc>
  <lastmod>2026-05-03T05:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軸索遅延が多層ネットワークの構造発達に与える影響（Impact of axonal delay on structure development in a multi-layered network）</news:title>
   <news:publication_date>2026-05-03T05:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685982</loc>
  <lastmod>2026-05-03T04:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量優先度付けによるマッチングと機械学習による統計調整の比較（Comparing Covariate Prioritization via Matching to Machine Learning Methods for Causal Inference using Five Empirical Applications）</news:title>
   <news:publication_date>2026-05-03T04:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685980</loc>
  <lastmod>2026-05-03T04:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間暖房の最適制御に向けた深層強化学習の応用（Deep Reinforcement Learning for Optimal Control of Space Heating）</news:title>
   <news:publication_date>2026-05-03T04:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685978</loc>
  <lastmod>2026-05-03T04:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-space深層学習による高速MRI補間（k-Space Deep Learning for Accelerated MRI）</news:title>
   <news:publication_date>2026-05-03T04:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685976</loc>
  <lastmod>2026-05-03T04:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cr2O3における原子間隙拡散の第一原理解析（A First Principles Investigation of Native Interstitial Diffusion in Cr2O3）</news:title>
   <news:publication_date>2026-05-03T04:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685974</loc>
  <lastmod>2026-05-03T04:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラジアルな方位選択性の出現：層状ネットワークにおける細胞密度変化と偏心の影響（Emergence of radial orientation selectivity: Effect of cell density changes and eccentricity in a layered network）</news:title>
   <news:publication_date>2026-05-03T04:31:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685972</loc>
  <lastmod>2026-05-03T04:30:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転写因子とDNA結合の機械学習アンサンブル（Transcription Factor-DNA Binding Via Machine Learning Ensembles）</news:title>
   <news:publication_date>2026-05-03T04:30:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685970</loc>
  <lastmod>2026-05-03T04:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話を意識したニューラル報酬による一貫性の高い文章生成（Discourse-Aware Neural Rewards for Coherent Text Generation）</news:title>
   <news:publication_date>2026-05-03T04:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685968</loc>
  <lastmod>2026-05-03T03:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータネットワークトラフィックにおける異常検知のためのシーケンス集約規則（Sequence Aggregation Rules for Anomaly Detection in Computer Network Traffic）</news:title>
   <news:publication_date>2026-05-03T03:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685966</loc>
  <lastmod>2026-05-03T03:39:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャッシュを計算資源に変える発想―メモリ内でDNN推論を高速化するNeural Cache（Neural Cache: Bit-Serial In-Cache Acceleration of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-03T03:39:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685964</loc>
  <lastmod>2026-05-03T03:38:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNeXtの構造と実践的評価（Evaluating ResNeXt Model Architecture for Image Classification）</news:title>
   <news:publication_date>2026-05-03T03:38:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685962</loc>
  <lastmod>2026-05-03T03:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞組織画像の高速かつ高精度な腫瘍セグメンテーション（Fast and Accurate Tumor Segmentation of Histology Images using Persistent Homology and Deep Convolutional Features）</news:title>
   <news:publication_date>2026-05-03T03:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685960</loc>
  <lastmod>2026-05-03T03:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブワード情報を組み込んだ行列分解型単語埋め込み（Incorporating Subword Information into Matrix Factorization Word Embeddings）</news:title>
   <news:publication_date>2026-05-03T03:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685958</loc>
  <lastmod>2026-05-03T03:37:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMは重みつき和を動的に計算する装置である（Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum）</news:title>
   <news:publication_date>2026-05-03T03:37:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685956</loc>
  <lastmod>2026-05-03T02:46:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オリオン星雲クラスターにおける原始惑星系円盤の性質（PROTOPLANETARY DISK PROPERTIES IN THE ORION NEBULA CLUSTER: INITIAL RESULTS FROM DEEP, HIGH-RESOLUTION ALMA OBSERVATIONS）</news:title>
   <news:publication_date>2026-05-03T02:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685954</loc>
  <lastmod>2026-05-03T02:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FIGSによる大質量銀河の星形成履歴解析（FIGS: Spectral fitting constraints on the star formation history of massive galaxies since Cosmic Noon）</news:title>
   <news:publication_date>2026-05-03T02:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685952</loc>
  <lastmod>2026-05-03T02:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベケンシュタインによるブラックホール面積の量子化（Bekenstein Quantization of Black-Hole Surface Area）</news:title>
   <news:publication_date>2026-05-03T02:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685950</loc>
  <lastmod>2026-05-03T02:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしバイリンガル辞書誘導の限界（On the Limitations of Unsupervised Bilingual Dictionary Induction）</news:title>
   <news:publication_date>2026-05-03T02:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685948</loc>
  <lastmod>2026-05-03T02:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水道管破裂リスクの機械学習評価と予防（Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks）</news:title>
   <news:publication_date>2026-05-03T02:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685946</loc>
  <lastmod>2026-05-03T01:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム神経ネットワークにおける結合から集合的動力学へ（From synaptic interactions to collective dynamics in random neuronal networks models: Critical role of eigenvectors and transient behavior）</news:title>
   <news:publication_date>2026-05-03T01:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685944</loc>
  <lastmod>2026-05-03T01:51:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延宇宙膨張のモデル非依存的評価の改良（An improved model-independent assessment of the late-time cosmic expansion）</news:title>
   <news:publication_date>2026-05-03T01:51:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685942</loc>
  <lastmod>2026-05-03T01:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測定数が変動する状況下におけるフーリエ・プチグラフィーの位相復元（Phase retrieval for Fourier Ptychography under varying amount of measurements）</news:title>
   <news:publication_date>2026-05-03T01:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685940</loc>
  <lastmod>2026-05-03T01:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドにおける協調作業の強化学習（Learning Coordinated Tasks using Reinforcement Learning in Humanoids）</news:title>
   <news:publication_date>2026-05-03T01:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685938</loc>
  <lastmod>2026-05-03T01:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTにおける協調オンライン学習によるモバイルエッジコンピューティングの安全性（Secure Mobile Edge Computing in IoT via Collaborative Online Learning）</news:title>
   <news:publication_date>2026-05-03T01:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685936</loc>
  <lastmod>2026-05-03T01:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドの重奏音響イベント検出（End-to-End Polyphonic Sound Event Detection）</news:title>
   <news:publication_date>2026-05-03T01:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685934</loc>
  <lastmod>2026-05-03T01:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次優位情報を用いた方策最適化（Policy Optimization with Second-Order Advantage Information）</news:title>
   <news:publication_date>2026-05-03T01:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685932</loc>
  <lastmod>2026-05-03T00:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的マルウェアに対する堅牢性の視覚的特徴（On Visual Hallmarks of Robustness to Adversarial Malware）</news:title>
   <news:publication_date>2026-05-03T00:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685930</loc>
  <lastmod>2026-05-03T00:57:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層信念ネットワークによる話者認識の示唆（Speaker Recognition using Deep Belief Networks）</news:title>
   <news:publication_date>2026-05-03T00:57:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685928</loc>
  <lastmod>2026-05-03T00:57:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーカミオカンデ検出器の設計と意義（Design of the Hyper-Kamiokande Detector）</news:title>
   <news:publication_date>2026-05-03T00:57:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685926</loc>
  <lastmod>2026-05-03T00:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散に基づくネットワーク埋め込み（Diffusion Based Network Embedding）</news:title>
   <news:publication_date>2026-05-03T00:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685924</loc>
  <lastmod>2026-05-03T00:56:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の筋活動を同時に場所と強さで推定する手法（Joint Action Unit localisation and intensity estimation through heatmap regression）</news:title>
   <news:publication_date>2026-05-03T00:56:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685922</loc>
  <lastmod>2026-05-03T00:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルによる深層ニューラルネットワークの統一枠組み（A Unified Framework of Deep Neural Networks by Capsules）</news:title>
   <news:publication_date>2026-05-03T00:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685920</loc>
  <lastmod>2026-05-03T00:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparse SfM深度事前知識を用いたDeep 2.5D車両分類（Deep 2.5D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems）</news:title>
   <news:publication_date>2026-05-03T00:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685918</loc>
  <lastmod>2026-05-03T00:04:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子状態識別のための最適普遍学習機（Optimal universal learning machines for quantum state discrimination）</news:title>
   <news:publication_date>2026-05-03T00:04:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685916</loc>
  <lastmod>2026-05-03T00:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習で光学情報記録の限界を押し広げる（Pushing the limits of optical information storage using deep learning）</news:title>
   <news:publication_date>2026-05-03T00:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685914</loc>
  <lastmod>2026-05-03T00:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリ変数と整数変数を含むベイズ最適化の扱い（Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-05-03T00:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685912</loc>
  <lastmod>2026-05-03T00:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパイラ最適化における機械学習の適用（Machine Learning in Compiler Optimisation）</news:title>
   <news:publication_date>2026-05-03T00:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685910</loc>
  <lastmod>2026-05-03T00:03:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワーク層の入力特徴マップでプライバシー損失を制御する手法（Controlling the privacy loss with the input feature maps of the layers in convolutional neural networks）</news:title>
   <news:publication_date>2026-05-03T00:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685908</loc>
  <lastmod>2026-05-03T00:03:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間質量巨星と超巨星の深層に迫る知見（Deep secrets of intermediate-mass giants and supergiants）</news:title>
   <news:publication_date>2026-05-03T00:03:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685906</loc>
  <lastmod>2026-05-02T23:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みプロトタイプ学習による頑健な分類（Robust Classification with Convolutional Prototype Learning）</news:title>
   <news:publication_date>2026-05-02T23:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685904</loc>
  <lastmod>2026-05-02T23:11:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコーディング・デコーダー：教師なし類似性タスクのための最適表現空間の探索（DECODING DECODERS: FINDING OPTIMAL REPRESENTATION SPACES FOR UNSUPERVISED SIMILARITY TASKS）</news:title>
   <news:publication_date>2026-05-02T23:11:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685902</loc>
  <lastmod>2026-05-02T23:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方向データに強い確率的深層モデルによる姿勢推定（Deep Directional Statistics: Pose Estimation with Uncertainty Quantification）</news:title>
   <news:publication_date>2026-05-02T23:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685900</loc>
  <lastmod>2026-05-02T23:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTボットネット攻撃のネットワーク検知に関する自動検出手法の要点（N-BaIoT: Network-based Detection of IoT Botnet Attacks Using Deep Autoencoders）</news:title>
   <news:publication_date>2026-05-02T23:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685898</loc>
  <lastmod>2026-05-02T23:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレア予測の深層学習モデル（DEEP FLARE NET (DeFN) MODEL FOR SOLAR FLARE PREDICTION）</news:title>
   <news:publication_date>2026-05-02T23:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685896</loc>
  <lastmod>2026-05-02T23:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ溝における連続的凝縮（Continuous condensation in nanogrooves）</news:title>
   <news:publication_date>2026-05-02T23:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685894</loc>
  <lastmod>2026-05-02T23:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルランキングモデルのドメイン横断正則化（Cross Domain Regularization for Neural Ranking Models using Adversarial Learning）</news:title>
   <news:publication_date>2026-05-02T23:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685892</loc>
  <lastmod>2026-05-02T22:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像の高解像度化をGANで実現する試み（PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-sharpening）</news:title>
   <news:publication_date>2026-05-02T22:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685890</loc>
  <lastmod>2026-05-02T22:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別器の表現を多様化してGANの学習を安定化する手法（IMPROVING GAN TRAINING VIA BINARIZED REPRESENTATION ENTROPY (BRE) REGULARIZATION）</news:title>
   <news:publication_date>2026-05-02T22:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685888</loc>
  <lastmod>2026-05-02T22:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダとニューラル決定森林による意見不正検出（Opinion Fraud Detection via Neural Autoencoder Decision Forest）</news:title>
   <news:publication_date>2026-05-02T22:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685886</loc>
  <lastmod>2026-05-02T22:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HMIの疑似連続光解釈（Understanding the HMI pseudocontinuum in white-light solar flares）</news:title>
   <news:publication_date>2026-05-02T22:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685884</loc>
  <lastmod>2026-05-02T22:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的コントラスト推定（Adversarial Contrastive Estimation）</news:title>
   <news:publication_date>2026-05-02T22:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685882</loc>
  <lastmod>2026-05-02T22:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepWalkingによるスマートフォン歩行速度推定（DeepWalking: Enabling Smartphone-based Walking Speed Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-05-02T22:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685880</loc>
  <lastmod>2026-05-02T22:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教えることを学ぶ――Learning to Teach（Learning to Teach）</news:title>
   <news:publication_date>2026-05-02T22:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685878</loc>
  <lastmod>2026-05-02T21:15:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源言語の語彙埋め込みを学習するPU学習の提案（Learning Word Embeddings for Low-resource Languages by PU Learning）</news:title>
   <news:publication_date>2026-05-02T21:15:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685876</loc>
  <lastmod>2026-05-02T21:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるアトラクタ再構築（Attractor Reconstruction by Machine Learning）</news:title>
   <news:publication_date>2026-05-02T21:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685874</loc>
  <lastmod>2026-05-02T21:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアンネットワーク分類器の説明に関する記号的アプローチ（A Symbolic Approach to Explaining Bayesian Network Classifiers）</news:title>
   <news:publication_date>2026-05-02T21:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685872</loc>
  <lastmod>2026-05-02T21:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意認識合成ネットワークによる人物再識別（Attention-Aware Compositional Network for Person Re-identification）</news:title>
   <news:publication_date>2026-05-02T21:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685870</loc>
  <lastmod>2026-05-02T21:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPG-Net: セグメンテーション予測と誘導による画像インペインティング（SPG-Net: Segmentation Prediction and Guidance Network for Image Inpainting）</news:title>
   <news:publication_date>2026-05-02T21:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685868</loc>
  <lastmod>2026-05-02T21:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムリスタを用いた教師なしニューロモルフィックシステムによる高速・省電力GAN実現（A Memristor based Unsupervised Neuromorphic System Towards Fast and Energy-Efficient GAN）</news:title>
   <news:publication_date>2026-05-02T21:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685866</loc>
  <lastmod>2026-05-02T21:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬推定による深層強化学習の分散削減（Reward Estimation for Variance Reduction in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-02T21:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685864</loc>
  <lastmod>2026-05-02T20:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間とロボットの協働を守る「監督者の安全集合」を学ぶ（Modeling Supervisor Safe Sets for Improving Collaboration in Human-Robot Teams）</news:title>
   <news:publication_date>2026-05-02T20:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685862</loc>
  <lastmod>2026-05-02T20:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多尺度計量による自己組織化マップの構造解析（Multi-scale metrics and self-organizing maps: a computational approach to the structure of sensory maps）</news:title>
   <news:publication_date>2026-05-02T20:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685860</loc>
  <lastmod>2026-05-02T20:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Network Enhancementによる生物ネットワークのノイズ除去（Network Enhancement: a general method to denoise weighted biological networks）</news:title>
   <news:publication_date>2026-05-02T20:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685858</loc>
  <lastmod>2026-05-02T20:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程予測のVecchia近似 (Vecchia approximations of Gaussian-process predictions)</news:title>
   <news:publication_date>2026-05-02T20:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685856</loc>
  <lastmod>2026-05-02T20:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子ども向け音声認識への成人モデルの転移学習（Transfer Learning from Adult to Children for Speech Recognition: Evaluation, Analysis and Recommendations）</news:title>
   <news:publication_date>2026-05-02T20:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685854</loc>
  <lastmod>2026-05-02T20:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス正規化が示した単一画像デヘイズの有効性（The Effectiveness of Instance Normalization: a Strong Baseline for Single Image Dehazing）</news:title>
   <news:publication_date>2026-05-02T20:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685852</loc>
  <lastmod>2026-05-02T19:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数帯域フィルタを用いた高い拡張性を持つ画像再構成（Highly Scalable Image Reconstruction using Deep Neural Networks with Bandpass Filtering）</news:title>
   <news:publication_date>2026-05-02T19:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685850</loc>
  <lastmod>2026-05-02T19:25:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド注意機構による音声認識の改善（Improved training of end-to-end attention models for speech recognition）</news:title>
   <news:publication_date>2026-05-02T19:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685848</loc>
  <lastmod>2026-05-02T19:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適なチーム編成のための深層ニューラルネットワーク（Deep Neural Networks for Optimal Team Composition）</news:title>
   <news:publication_date>2026-05-02T19:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685846</loc>
  <lastmod>2026-05-02T19:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙資源に未収録の語へ意味情報を広げる後処理（Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources）</news:title>
   <news:publication_date>2026-05-02T19:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685844</loc>
  <lastmod>2026-05-02T19:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ属性を取り込むネットワーク埋め込みの進化（Capturing Edge Attributes via Network Embedding）</news:title>
   <news:publication_date>2026-05-02T19:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685842</loc>
  <lastmod>2026-05-02T19:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像における高反射小斑点の完全自動セグメンテーション（Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images）</news:title>
   <news:publication_date>2026-05-02T19:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685840</loc>
  <lastmod>2026-05-02T19:23:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャンプを伴うランダムウォークの緩和時間の解析（Analysis of Relaxation Time in Random Walk with Jumps）</news:title>
   <news:publication_date>2026-05-02T19:23:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685838</loc>
  <lastmod>2026-05-02T18:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペア付きと非ペア付きトレーニングを同時に用いた画像変換学習（Learning image-to-image translation using paired and unpaired training samples）</news:title>
   <news:publication_date>2026-05-02T18:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685836</loc>
  <lastmod>2026-05-02T18:32:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>礼節を保つ対話生成――並列データなしで礼儀正しい応答を作る方法（Polite Dialogue Generation Without Parallel Data）</news:title>
   <news:publication_date>2026-05-02T18:32:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685834</loc>
  <lastmod>2026-05-02T18:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度医用画像合成における漸進的生成対向ネットワークの応用（High-resolution medical image synthesis using progressively grown generative adversarial networks）</news:title>
   <news:publication_date>2026-05-02T18:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685832</loc>
  <lastmod>2026-05-02T18:31:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス確率場の局所的代数的簡約化（Local, algebraic simplifications of Gaussian random fields）</news:title>
   <news:publication_date>2026-05-02T18:31:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685830</loc>
  <lastmod>2026-05-02T18:31:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模空間データにおける確率密度関数の並列計算（Parallel Computation of PDFs on Big Spatial Data Using Spark）</news:title>
   <news:publication_date>2026-05-02T18:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685828</loc>
  <lastmod>2026-05-02T18:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深紫外から中赤外までのスーパーコンティニューム生成（Deep-UV to mid-IR supercontinuum generation driven by mid-IR ultrashort pulses in a gas-filled fiber）</news:title>
   <news:publication_date>2026-05-02T18:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685826</loc>
  <lastmod>2026-05-02T18:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合イニシアティブとマルチモーダルフィードバックによる画像検索（Image Retrieval with Mixed Initiative and Multimodal Feedback）</news:title>
   <news:publication_date>2026-05-02T18:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685824</loc>
  <lastmod>2026-05-02T17:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Connection Tableauxにおける機械学習ガイダンスと証明認証（Machine Learning Guidance and Proof Certification for Connection Tableaux）</news:title>
   <news:publication_date>2026-05-02T17:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685822</loc>
  <lastmod>2026-05-02T17:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界で学習するCNN（Learning on the Edge: Explicit Boundary Handling in CNNs）</news:title>
   <news:publication_date>2026-05-02T17:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685820</loc>
  <lastmod>2026-05-02T17:39:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体を自己学習するロボット：予測符号化による自己推定の実装（Adaptive robot body learning and estimation through predictive coding）</news:title>
   <news:publication_date>2026-05-02T17:39:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685818</loc>
  <lastmod>2026-05-02T17:38:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プーリングやストライドを含むCNNでの高速な密な特徴抽出（Fast Dense Feature Extraction with CNNs that have Pooling or Striding Layers）</news:title>
   <news:publication_date>2026-05-02T17:38:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685816</loc>
  <lastmod>2026-05-02T17:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動データにおける興味深いパターンの発見にSimpsonのパラドックスを用いる（Using Simpson’s Paradox to Discover Interesting Patterns in Behavioral Data）</news:title>
   <news:publication_date>2026-05-02T17:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685814</loc>
  <lastmod>2026-05-02T17:38:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M49のハローにおける三つの動的に異なる恒星集団（Three dynamically distinct stellar populations in the halo of M49）</news:title>
   <news:publication_date>2026-05-02T17:38:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685812</loc>
  <lastmod>2026-05-02T17:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適制御における欺瞞（Deception in Optimal Control）</news:title>
   <news:publication_date>2026-05-02T17:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685810</loc>
  <lastmod>2026-05-02T16:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的視点計画による物体再構成（Active Object Reconstruction Using a Guided View Planner）</news:title>
   <news:publication_date>2026-05-02T16:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685808</loc>
  <lastmod>2026-05-02T16:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ量子化を意識した深層ネットワークによる高精度・高速スパイキングニューロモーフィックシステム（Towards Accurate and High-Speed Spiking Neuromorphic Systems with Data Quantization-Aware Deep Networks）</news:title>
   <news:publication_date>2026-05-02T16:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685806</loc>
  <lastmod>2026-05-02T16:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Recurrent CNNによる3D視線推定（Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues）</news:title>
   <news:publication_date>2026-05-02T16:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685804</loc>
  <lastmod>2026-05-02T16:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光の軌道角運動量を誘起する非吸収光学素子の研究（Orbital Angular Momentum Induced by Nonabsorbing Optical Elements through Space-variant Polarization-state Manipulations）</news:title>
   <news:publication_date>2026-05-02T16:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685802</loc>
  <lastmod>2026-05-02T16:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値化された測定からのスパース復元を扱うBSBL（Binary Sparse Bayesian Learning Algorithm for One-bit Compressed Sensing）</news:title>
   <news:publication_date>2026-05-02T16:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685800</loc>
  <lastmod>2026-05-02T16:45:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MWC 758の円盤における塵の渦捕獲の可視化（Cm-wavelength observations of MWC 758: resolved dust trapping in a vortex）</news:title>
   <news:publication_date>2026-05-02T16:45:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685798</loc>
  <lastmod>2026-05-02T16:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaia DR2における新たな散開星団発見手法（A new method for unveiling Open Clusters in Gaia）</news:title>
   <news:publication_date>2026-05-02T16:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685796</loc>
  <lastmod>2026-05-02T15:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>E-Commerceレビューの統計解析と双方向RNNによる感情分類（Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network）</news:title>
   <news:publication_date>2026-05-02T15:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685794</loc>
  <lastmod>2026-05-02T15:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ペプチド同定のための効率的オンライン学習（Eﬃcient online learning for large-scale peptide identification）</news:title>
   <news:publication_date>2026-05-02T15:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685792</loc>
  <lastmod>2026-05-02T15:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリーに基づく深層CCAによる細粒度会場探索（Category-Based Deep CCA for Fine-Grained Venue Discovery from Multimodal Data）</news:title>
   <news:publication_date>2026-05-02T15:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685790</loc>
  <lastmod>2026-05-02T15:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モアレ模様除去のためのマルチレゾリューション畳み込みニューラルネットワーク（Moiré Photo Restoration Using Multiresolution Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-02T15:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685788</loc>
  <lastmod>2026-05-02T15:44:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期アルゴリズムを記述する微分方程式（Differential Equations for Modeling Asynchronous Algorithms）</news:title>
   <news:publication_date>2026-05-02T15:44:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685786</loc>
  <lastmod>2026-05-02T15:44:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形効用を持つ多項ロジット・バンディット（Multinomial Logit Bandit with Linear Utility Functions）</news:title>
   <news:publication_date>2026-05-02T15:44:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685784</loc>
  <lastmod>2026-05-02T15:43:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッションベース推薦におけるユーザー静的コンテキストの活用（Augmenting Recurrent Neural Networks with High-Order User-Contextual Preference for Session-Based Recommendation）</news:title>
   <news:publication_date>2026-05-02T15:43:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685782</loc>
  <lastmod>2026-05-02T14:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムリスタネットワークを用いた階層時系列記憶（Hierarchical Temporal Memory using Memristor Networks: A Survey）</news:title>
   <news:publication_date>2026-05-02T14:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685780</loc>
  <lastmod>2026-05-02T14:52:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の基本周波数（F0）推定を回帰で強化する手法（A Regression Model of Recurrent Deep Neural Networks for Noise Robust Estimation of the Fundamental Frequency Contour of Speech）</news:title>
   <news:publication_date>2026-05-02T14:52:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685778</loc>
  <lastmod>2026-05-02T14:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量データで音声指示を理解するカプセルネットワークの可能性（Capsule Networks for Low Resource Spoken Language Understanding）</news:title>
   <news:publication_date>2026-05-02T14:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685776</loc>
  <lastmod>2026-05-02T14:51:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>利益を上げるバンディット（Profitable Bandits）</news:title>
   <news:publication_date>2026-05-02T14:51:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685774</loc>
  <lastmod>2026-05-02T14:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるショートカット接続で物体カウントを改善する（Learning Short-Cut Connections for Object Counting）</news:title>
   <news:publication_date>2026-05-02T14:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685772</loc>
  <lastmod>2026-05-02T14:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力埋め込み空間における解釈可能な敵対的摂動（Interpretable Adversarial Perturbation in Input Embedding Space for Text）</news:title>
   <news:publication_date>2026-05-02T14:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685770</loc>
  <lastmod>2026-05-02T14:50:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全言語で使える評価軸：敵対的マルチタスク学習による多言語対話評価（One “Ruler” for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning）</news:title>
   <news:publication_date>2026-05-02T14:50:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685768</loc>
  <lastmod>2026-05-02T13:59:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続データにおける頻出エンティティの発見（Finding Frequent Entities in Continuous Data）</news:title>
   <news:publication_date>2026-05-02T13:59:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685766</loc>
  <lastmod>2026-05-02T13:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の序数分類と理解—マスキングラベル付きグリッドドロップアウト（Image Ordinal Classification and Understanding: Grid Dropout with Masking Label）</news:title>
   <news:publication_date>2026-05-02T13:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685764</loc>
  <lastmod>2026-05-02T13:49:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残り時間予測に関する総覧とクロスベンチマーク比較（Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring）</news:title>
   <news:publication_date>2026-05-02T13:49:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685762</loc>
  <lastmod>2026-05-02T13:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラピディティギャップ分布とパートン系譜の関係（Rapidity gap distribution in diffractive deep-inelastic scattering and parton genealogy）</news:title>
   <news:publication_date>2026-05-02T13:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685760</loc>
  <lastmod>2026-05-02T13:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tile2Vecによる空間データの教師なし表現学習（Tile2Vec: Unsupervised representation learning for spatially distributed data）</news:title>
   <news:publication_date>2026-05-02T13:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685758</loc>
  <lastmod>2026-05-02T13:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化超幾何分布（GHD）に基づく可識別な有向非巡回グラフモデル（Identifiability of Generalized Hypergeometric Distribution (GHD) Directed Acyclic Graphical Models）</news:title>
   <news:publication_date>2026-05-02T13:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685756</loc>
  <lastmod>2026-05-02T13:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン正規化器によるSoftmax高速化（Online normalizer calculation for softmax）</news:title>
   <news:publication_date>2026-05-02T13:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685754</loc>
  <lastmod>2026-05-02T12:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師ありビデオオブジェクトの言語に基づく位置推定（Weakly-Supervised Video Object Grounding from Text）</news:title>
   <news:publication_date>2026-05-02T12:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685752</loc>
  <lastmod>2026-05-02T12:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会計不正検出のための法務データ分析（Fighting Accounting Fraud Through Forensic Data Analytics）</news:title>
   <news:publication_date>2026-05-02T12:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685750</loc>
  <lastmod>2026-05-02T12:55:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRPCの時間再構築におけるニューラルネットワーク手法（A neural network based algorithm for MRPC time reconstruction）</news:title>
   <news:publication_date>2026-05-02T12:55:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685748</loc>
  <lastmod>2026-05-02T12:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チューン可能なGMMカーネルで木構造に迫る（Several Tunable GMM Kernels）</news:title>
   <news:publication_date>2026-05-02T12:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685746</loc>
  <lastmod>2026-05-02T12:55:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフェスト文書の階層的解析で細部と全体を同時に読む（Hierarchical Structured Model for Fine-to-coarse Manifesto Text Analysis）</news:title>
   <news:publication_date>2026-05-02T12:55:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685744</loc>
  <lastmod>2026-05-02T12:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLC NANDフラッシュメモリにおけるデータ保持エラーの実験的特性評価と回復手法（Experimental Characterization, Optimization, and Recovery of Data Retention Errors in MLC NAND Flash Memory）</news:title>
   <news:publication_date>2026-05-02T12:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685742</loc>
  <lastmod>2026-05-02T12:54:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web画像検索のインタラクション行動モデル構築（Constructing an Interaction Behavior Model for Web Image Search）</news:title>
   <news:publication_date>2026-05-02T12:54:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685740</loc>
  <lastmod>2026-05-02T12:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認証のなりすまし検知にCNNを使うと何が変わるか（A Performance Evaluation of Convolutional Neural Networks for Face Anti Spoofing）</news:title>
   <news:publication_date>2026-05-02T12:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685738</loc>
  <lastmod>2026-05-02T12:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Combo Loss: 入力と出力の不均衡を同時に扱う損失関数（Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation）</news:title>
   <news:publication_date>2026-05-02T12:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685736</loc>
  <lastmod>2026-05-02T12:02:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーデルの不完全性定理の新しい視点と応用（A new viewpoint of the Gödel’s incompleteness theorem and it’s applications）</news:title>
   <news:publication_date>2026-05-02T12:02:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685734</loc>
  <lastmod>2026-05-02T12:01:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファストオンライン精密解法：決定論的MDPのスパース報酬問題（Fast Online Exact Solutions for Deterministic MDPs with Sparse Rewards）</news:title>
   <news:publication_date>2026-05-02T12:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685732</loc>
  <lastmod>2026-05-02T12:01:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画の要所だけをリアルタイムで抜き出す技術――FFNetによるオンライン高速再生（FFNet: Video Fast-Forwarding via Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-02T12:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685730</loc>
  <lastmod>2026-05-02T12:01:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層敵対的学習による微細構造材料設計（Microstructural Materials Design via Deep Adversarial Learning Methodology）</news:title>
   <news:publication_date>2026-05-02T12:01:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685728</loc>
  <lastmod>2026-05-02T12:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReGANによる系列生成と勾配推定の比較（ReGAN: RE[LAX&amp;#124;BAR&amp;#124;INFORCE] based Sequence Generation using GANs）</news:title>
   <news:publication_date>2026-05-02T12:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685726</loc>
  <lastmod>2026-05-02T11:08:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションを活用して二足歩行ロボットのベイズ最適化を効率化する手法（Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots）</news:title>
   <news:publication_date>2026-05-02T11:08:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685724</loc>
  <lastmod>2026-05-02T11:01:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロ構造再現と構造—物性予測への転移学習アプローチ（A Transfer Learning Approach for Microstructure Reconstruction and Structure-property Predictions）</news:title>
   <news:publication_date>2026-05-02T11:01:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685722</loc>
  <lastmod>2026-05-02T11:01:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習されたプロトタイプ分類器によるエンドツーエンドリファインメント（End-to-End Refinement Guided by Pre-trained Prototypical Classifier）</news:title>
   <news:publication_date>2026-05-02T11:01:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685720</loc>
  <lastmod>2026-05-02T11:01:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発作性心房細動の検出にAttention付き双方向RNNを用いる手法（Detection of Paroxysmal Atrial Fibrillation using Attention-based Bidirectional Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-02T11:01:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685718</loc>
  <lastmod>2026-05-02T10:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に少ない陽性サンプルでの疾患検出アルゴリズム構築（Building Disease Detection Algorithms with Very Small Numbers of Positive Samples）</news:title>
   <news:publication_date>2026-05-02T10:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685716</loc>
  <lastmod>2026-05-02T10:59:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消費者向けIoT機器における圧縮プレーンテキスト検出（Detecting Compressed Cleartext Traffic from Consumer Internet of Things Devices）</news:title>
   <news:publication_date>2026-05-02T10:59:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685714</loc>
  <lastmod>2026-05-02T10:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張畳み込みとオクルージョン推論による光フロー学習 (LEARNING OPTICAL FLOW VIA DILATED NETWORKS AND OCCLUSION REASONING)</news:title>
   <news:publication_date>2026-05-02T10:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685712</loc>
  <lastmod>2026-05-02T10:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム回帰解析における深層畳み込みニューラルネットワーク（Real-time regression analysis with deep convolutional neural networks）</news:title>
   <news:publication_date>2026-05-02T10:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685710</loc>
  <lastmod>2026-05-02T10:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非二値関数に対するスパン・プログラムの一般化（Span programs for non-binary functions）</news:title>
   <news:publication_date>2026-05-02T10:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685708</loc>
  <lastmod>2026-05-02T10:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二状態リカレントネットワークによる画像超解像（Image Super-Resolution via Dual-State Recurrent Networks）</news:title>
   <news:publication_date>2026-05-02T10:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685706</loc>
  <lastmod>2026-05-02T10:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホラルキック構造による分散深層学習の性能解析（Holarchic Structures for Decentralized Deep Learning – A Performance Analysis）</news:title>
   <news:publication_date>2026-05-02T10:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685704</loc>
  <lastmod>2026-05-02T10:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ペイロードベースの難読化による侵入検知器のロバスト化（Improving Network Intrusion Detection Classifiers by Non-payload-Based Exploit-Independent Obfuscations: An Adversarial Approach）</news:title>
   <news:publication_date>2026-05-02T10:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685702</loc>
  <lastmod>2026-05-02T10:04:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21-cmトモグラフィーから学ぶ深層学習による宇宙の夜明けと再電離の推定（Deep learning from 21-cm tomography of the Cosmic Dawn and Reionization）</news:title>
   <news:publication_date>2026-05-02T10:04:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685700</loc>
  <lastmod>2026-05-02T10:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PolSARデータの領域ベース分類における確率的距離を用いた放射基底核関数（Region-Based Classification of PolSAR Data Using Radial Basis Kernel Functions With Stochastic Distances）</news:title>
   <news:publication_date>2026-05-02T10:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685698</loc>
  <lastmod>2026-05-02T09:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間赤方偏移にある大量パッシブ銀河の分子ガスとスケーリング関係（Molecular Gas Contents and Scaling Relations for Massive Passive Galaxies at Intermediate Redshifts from the LEGA-C Survey）</news:title>
   <news:publication_date>2026-05-02T09:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685696</loc>
  <lastmod>2026-05-02T09:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一層隠れ層ニューラルネットワークの勾配降下法収束性（Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds）</news:title>
   <news:publication_date>2026-05-02T09:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685694</loc>
  <lastmod>2026-05-02T09:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラージ・マジェラン雲の超外縁に広がる微光の星々（Exploring the Very Extended Low Surface Brightness Stellar Populations of the Large Magellanic Cloud with SMASH）</news:title>
   <news:publication_date>2026-05-02T09:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685692</loc>
  <lastmod>2026-05-02T09:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力レンズで見つける遠方超新星 — LSSTによるz∼5–7での検出可能性の評価（Detecting strongly lensed supernovae at z ∼5–7 with LSST）</news:title>
   <news:publication_date>2026-05-02T09:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685690</loc>
  <lastmod>2026-05-02T09:02:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定木ブースティングのウェーブレット分解による改良（Wavelet Decomposition of Gradient Boosting）</news:title>
   <news:publication_date>2026-05-02T09:02:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685688</loc>
  <lastmod>2026-05-02T09:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Label RefineryによるImageNet分類の精度向上（Label Refinery: Improving ImageNet Classification through Label Progression）</news:title>
   <news:publication_date>2026-05-02T09:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685686</loc>
  <lastmod>2026-05-02T09:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共鳴する未知物理の異常検出──機械学習によるモデル非依存的なバンプハントの拡張（Anomaly Detection for Resonant New Physics with Machine Learning）</news:title>
   <news:publication_date>2026-05-02T09:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685684</loc>
  <lastmod>2026-05-02T08:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程回帰を用いて効率化したアブイニシオ・インスタントン反応率理論 (Ab initio instanton rate theory made efficient using Gaussian process regression)</news:title>
   <news:publication_date>2026-05-02T08:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685682</loc>
  <lastmod>2026-05-02T08:01:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3ループにおけるグルージョンジェット関数の計算（Gluon jet function at three loops in QCD）</news:title>
   <news:publication_date>2026-05-02T08:01:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685680</loc>
  <lastmod>2026-05-02T08:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>API経由のモデル窃取を検知する実践的アプローチ（PRADA: Protecting Against DNN Model Stealing Attacks）</news:title>
   <news:publication_date>2026-05-02T08:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685678</loc>
  <lastmod>2026-05-02T08:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shattering係数の計算が示す学習保証の本質（Computing the Shattering Coefficient of Supervised Learning Algorithms）</news:title>
   <news:publication_date>2026-05-02T08:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685676</loc>
  <lastmod>2026-05-02T07:59:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数条件の遺伝子規制ネットワークを高速に統合推定する手法の要点（Fast Bayesian Integrative Learning of Multiple Gene Regulatory Networks for Type 1 Diabetes）</news:title>
   <news:publication_date>2026-05-02T07:59:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685674</loc>
  <lastmod>2026-05-02T07:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所可算準確率測度保存に近いグラフの点別エルゴード定理（Pointwise Ergodic Theorem for Locally Countable Quasi-PMP Graphs）</news:title>
   <news:publication_date>2026-05-02T07:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685672</loc>
  <lastmod>2026-05-02T07:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声の連続的ピッチ補正をデータ駆動で実現する手法（A DATA-DRIVEN APPROACH TO SMOOTH PITCH CORRECTION FOR SINGING VOICE IN POP MUSIC）</news:title>
   <news:publication_date>2026-05-02T07:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685670</loc>
  <lastmod>2026-05-02T07:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係性ネットワークによる骨格ベースの行動認識（Relational Network for Skeleton-Based Action Recognition）</news:title>
   <news:publication_date>2026-05-02T07:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685668</loc>
  <lastmod>2026-05-02T07:07:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純なランダムフォレストモデルの鋭い解析（Sharp analysis of a simple model for random forests）</news:title>
   <news:publication_date>2026-05-02T07:07:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685666</loc>
  <lastmod>2026-05-02T07:07:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種データから遺伝子制御ネットワークを同時に学ぶ手法（Learning Gene Regulatory Networks with High-Dimensional Heterogeneous Data）</news:title>
   <news:publication_date>2026-05-02T07:07:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685664</loc>
  <lastmod>2026-05-02T07:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市民による流域評価の可能性—定性的判断を市民科学者に訓練できるか（Appraising Human Impact on Watersheds: The Feasibility of Training Citizen Scientists to make Qualitative Judgments）</news:title>
   <news:publication_date>2026-05-02T07:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685662</loc>
  <lastmod>2026-05-02T07:05:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き文書の行分割を確率的に解く枠組み（A probabilistic framework for handwritten text line segmentation）</news:title>
   <news:publication_date>2026-05-02T07:05:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685660</loc>
  <lastmod>2026-05-02T07:05:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DC回路のための3D出力可能な高さモデル（3D-Printable Height Models for DC Circuits）</news:title>
   <news:publication_date>2026-05-02T07:05:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685658</loc>
  <lastmod>2026-05-02T07:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信号機検出におけるSingle Shot Detectionの適用（Detecting Traffic Lights by Single Shot Detection）</news:title>
   <news:publication_date>2026-05-02T07:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685656</loc>
  <lastmod>2026-05-02T06:12:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック・ネットワーク・ラッソの意義と実用性（The Logistic Network Lasso）</news:title>
   <news:publication_date>2026-05-02T06:12:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685654</loc>
  <lastmod>2026-05-02T06:12:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QARC：動画品質を意識したレート制御（QARC: Video Quality Aware Rate Control for Real-Time Video Streaming via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-02T06:12:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685652</loc>
  <lastmod>2026-05-02T06:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MEGAN：マルチモーダル画像生成のための専門家混合GAN（Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation）</news:title>
   <news:publication_date>2026-05-02T06:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685650</loc>
  <lastmod>2026-05-02T06:10:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>侵襲低減手術における器具セグメンテーションと追跡の比較評価 (Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery)</news:title>
   <news:publication_date>2026-05-02T06:10:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685648</loc>
  <lastmod>2026-05-02T06:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所空間情報を取り込む順序基準ハッシュ学習（Deep Ordinal Hashing with Spatial Attention）</news:title>
   <news:publication_date>2026-05-02T06:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685646</loc>
  <lastmod>2026-05-02T06:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ドメイン間で対応する画像を生成する手法（Unpaired Multi-Domain Image Generation via Regularized Conditional GANs）</news:title>
   <news:publication_date>2026-05-02T06:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685644</loc>
  <lastmod>2026-05-02T06:09:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を同時に扱う文センテンス表現：Sentence-State LSTM（Sentence-State LSTM for Text Representation）</news:title>
   <news:publication_date>2026-05-02T06:09:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685642</loc>
  <lastmod>2026-05-02T05:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純な制約で知識グラフ埋め込みを改善する（Improving Knowledge Graph Embedding Using Simple Constraints）</news:title>
   <news:publication_date>2026-05-02T05:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685640</loc>
  <lastmod>2026-05-02T05:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークコミュニティの優先順位付け (Prioritizing network communities)</news:title>
   <news:publication_date>2026-05-02T05:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685638</loc>
  <lastmod>2026-05-02T05:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非摂動的な横運動量（TMD）効果の実験的検証と因子化違反の示唆（Nonperturbative transverse-momentum-dependent effects in dihadron and direct photon-hadron angular correlations in p+p collisions at √s = 200 GeV）</news:title>
   <news:publication_date>2026-05-02T05:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685636</loc>
  <lastmod>2026-05-02T05:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMDenseLSTMによる音源分離の高効率化（MMDENSELSTM: AN EFFICIENT COMBINATION OF CONVOLUTIONAL AND RECURRENT NEURAL NETWORKS FOR AUDIO SOURCE SEPARATION）</news:title>
   <news:publication_date>2026-05-02T05:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685634</loc>
  <lastmod>2026-05-02T05:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な表示レイアウトにおける関連性と表示の好みのランキング（Ranking for Relevance and Display Preferences in Complex Presentation Layouts）</news:title>
   <news:publication_date>2026-05-02T05:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685632</loc>
  <lastmod>2026-05-02T05:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索タスクにおける視線追跡と知識変化の関連（Relating Eye-Tracking Measures With Changes In Knowledge on Search Tasks）</news:title>
   <news:publication_date>2026-05-02T05:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685630</loc>
  <lastmod>2026-05-02T05:07:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワーク埋め込みを現実に変えた手法（Billion-scale Network Embedding with Iterative Random Projection）</news:title>
   <news:publication_date>2026-05-02T05:07:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685628</loc>
  <lastmod>2026-05-02T04:16:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングに基づく人工ディスパッチャの概念（The Concept of the Deep Learning-Based System Artificial Dispatcher to Power System Control and Dispatch）</news:title>
   <news:publication_date>2026-05-02T04:16:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685626</loc>
  <lastmod>2026-05-02T04:16:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフ事実の弱監視的文脈化（Weakly-supervised Contextualization of Knowledge Graph Facts）</news:title>
   <news:publication_date>2026-05-02T04:16:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685624</loc>
  <lastmod>2026-05-02T04:16:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによる医療画像の弾性登録（ELASTIC REGISTRATION OF MEDICAL IMAGES WITH GANS）</news:title>
   <news:publication_date>2026-05-02T04:16:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685622</loc>
  <lastmod>2026-05-02T04:16:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を用いたマルチモーダル機械翻訳が示した実務的示唆（Multimodal Machine Translation with Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-02T04:16:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685620</loc>
  <lastmod>2026-05-02T04:15:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース半空間の効率的アクティブラーニング（Efficient Active Learning of Sparse Halfspaces）</news:title>
   <news:publication_date>2026-05-02T04:15:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685618</loc>
  <lastmod>2026-05-02T04:15:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的行動セットによる計画と学習（Planning and Learning with Stochastic Action Sets）</news:title>
   <news:publication_date>2026-05-02T04:15:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685616</loc>
  <lastmod>2026-05-02T04:15:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pにおける精密困難性と対話式証明の接点（Fine-grained Complexity Meets IP = PSPACE）</news:title>
   <news:publication_date>2026-05-02T04:15:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685614</loc>
  <lastmod>2026-05-02T03:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ページ単位推薦のための深層強化学習（Deep Reinforcement Learning for Page-wise Recommendations）</news:title>
   <news:publication_date>2026-05-02T03:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685612</loc>
  <lastmod>2026-05-02T03:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関ランダムグラフ上のほぼ効率的なグラフマッチングアルゴリズム（(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs）</news:title>
   <news:publication_date>2026-05-02T03:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685610</loc>
  <lastmod>2026-05-02T03:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗法ノイズを加法誤差へ近似する手法（An Additive Approximation to Multiplicative Noise）</news:title>
   <news:publication_date>2026-05-02T03:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685608</loc>
  <lastmod>2026-05-02T03:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子回路の幾何学と電磁雑音への影響（The Geometry of a Quantum Circuit and its Impact on Electromagnetic Noise）</news:title>
   <news:publication_date>2026-05-02T03:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685606</loc>
  <lastmod>2026-05-02T03:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ローカル分類器チェーンによるマッチング手法（A Hierarchical Matcher using Local Classifier Chains）</news:title>
   <news:publication_date>2026-05-02T03:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685604</loc>
  <lastmod>2026-05-02T03:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>骨格ベース動作認識の新展開（Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning）</news:title>
   <news:publication_date>2026-05-02T03:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685602</loc>
  <lastmod>2026-05-02T03:13:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyTorchにおける確率的準ニュートン法の実装（Implementation of Stochastic Quasi-Newton’s Method in PyTorch）</news:title>
   <news:publication_date>2026-05-02T03:13:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685600</loc>
  <lastmod>2026-05-02T02:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半直交非負行列因子分解（Semi-Orthogonal Non-Negative Matrix Factorization）</news:title>
   <news:publication_date>2026-05-02T02:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685598</loc>
  <lastmod>2026-05-02T02:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり学習で応答選択精度を高める手法の要点（Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots）</news:title>
   <news:publication_date>2026-05-02T02:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685596</loc>
  <lastmod>2026-05-02T02:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で見出した高性能スピン駆動熱電材料（Machine-learning guided discovery of a high-performance spin-driven thermoelectric material）</news:title>
   <news:publication_date>2026-05-02T02:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685594</loc>
  <lastmod>2026-05-02T02:20:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理学学習に対する態度と動機付けの関係（Attitude and Motivation towards Learning Physics）</news:title>
   <news:publication_date>2026-05-02T02:20:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685592</loc>
  <lastmod>2026-05-02T02:20:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴抽出におけるニューラルネットワークの活用の検証（Examining the Use of Neural Networks for Feature Extraction: A Comparative Analysis using Deep Learning, Support Vector Machines, and K-Nearest Neighbor Classifiers）</news:title>
   <news:publication_date>2026-05-02T02:20:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685590</loc>
  <lastmod>2026-05-02T02:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LIGOデータのクラスタリングのための深層識別埋め込み（DIRECT: DEEP DISCRIMINATIVE EMBEDDING FOR CLUSTERING OF LIGO DATA）</news:title>
   <news:publication_date>2026-05-02T02:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685588</loc>
  <lastmod>2026-05-02T02:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対(ペア)関係を取り込む生成的クラスタリング（Clustering With Pairwise Relationships: A Generative Approach）</news:title>
   <news:publication_date>2026-05-02T02:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685586</loc>
  <lastmod>2026-05-02T01:27:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ID文書写真とセルフィーの照合を現実にするDocFace（DocFace: Matching ID Document Photos to Selfies）</news:title>
   <news:publication_date>2026-05-02T01:27:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685584</loc>
  <lastmod>2026-05-02T01:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単発単一スケールによる肺結節検出（S4ND: Single-Shot Single-Scale Lung Nodule Detection）</news:title>
   <news:publication_date>2026-05-02T01:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685582</loc>
  <lastmod>2026-05-02T01:27:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ正則化によるグラフモデル推定（Bayesian Regularization for Graphical Models with Unequal Shrinkage）</news:title>
   <news:publication_date>2026-05-02T01:27:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685580</loc>
  <lastmod>2026-05-02T01:27:10Z</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到達可能性解析（Reachability Analysis of Deep Neural Networks with Provable Guarantees）</news:title>
   <news:publication_date>2026-05-02T01:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685578</loc>
  <lastmod>2026-05-02T01:27:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ベースのファッション商品推薦（Image Based Fashion Product Recommendation with Deep Learning）</news:title>
   <news:publication_date>2026-05-02T01:27:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685576</loc>
  <lastmod>2026-05-02T01:26:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習時にのみ得られる情報を利用した異常検知の拡張（Incorporating Privileged Information to Unsupervised Anomaly Detection）</news:title>
   <news:publication_date>2026-05-02T01:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685574</loc>
  <lastmod>2026-05-02T00:35:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文から単語ラベルを推定するゼロショット系列ラベリング（Zero-shot Sequence Labeling: Transferring Knowledge from Sentences to Tokens）</news:title>
   <news:publication_date>2026-05-02T00:35:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685572</loc>
  <lastmod>2026-05-02T00:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散化した因子分解機による高速特徴量ベース推薦（Discrete Factorization Machines for Fast Feature-based Recommendation）</news:title>
   <news:publication_date>2026-05-02T00:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685570</loc>
  <lastmod>2026-05-02T00:25:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FASKと介入知識による因果グラフ復元（FASK with Interventional Knowledge Recovers Edges from the Sachs Model）</news:title>
   <news:publication_date>2026-05-02T00:25:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685568</loc>
  <lastmod>2026-05-02T00:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BRCA1/BRCA2の未知変異を機械学習で判定する（Predicting clinical significance of BRCA1 and BRCA2 single nucleotide substitution variants with unknown clinical significance using probabilistic neural network and deep neural network-stacked autoencoder）</news:title>
   <news:publication_date>2026-05-02T00:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685566</loc>
  <lastmod>2026-05-02T00:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network（Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network）</news:title>
   <news:publication_date>2026-05-02T00:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685564</loc>
  <lastmod>2026-05-02T00:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル端末向け統合検索フレームワークの第一歩（Target Apps Selection: Towards a Unified Search Framework for Mobile Devices）</news:title>
   <news:publication_date>2026-05-02T00:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685562</loc>
  <lastmod>2026-05-02T00:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール顔復元のための逐次ゲーティングアンサンブルネットワーク（Multi-Scale Face Restoration with Sequential Gating Ensemble Network）</news:title>
   <news:publication_date>2026-05-02T00:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685560</loc>
  <lastmod>2026-05-01T23:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベート逐次学習（Private Sequential Learning）</news:title>
   <news:publication_date>2026-05-01T23:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685558</loc>
  <lastmod>2026-05-01T23:32:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オブジェクトコードの自動分類技術（Automatic Classification of Object Code Using Machine Learning）</news:title>
   <news:publication_date>2026-05-01T23:32:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685556</loc>
  <lastmod>2026-05-01T23:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デンドログラムを散布図に変える単純で速い手法：Branching Embedding（Branching embedding: A heuristic dimensionality reduction algorithm based on hierarchical clustering）</news:title>
   <news:publication_date>2026-05-01T23:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685554</loc>
  <lastmod>2026-05-01T23:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>名前の文字列から人種・民族を推定する手法の実用性と限界（Predicting Race and Ethnicity From the Sequence of Characters in a Name）</news:title>
   <news:publication_date>2026-05-01T23:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685552</loc>
  <lastmod>2026-05-01T23:30:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数で高精度を実現する強化学習ベースのアンサンブル選択（Developing parsimonious ensembles using ensemble diversity within a reinforcement learning framework）</news:title>
   <news:publication_date>2026-05-01T23:30:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685550</loc>
  <lastmod>2026-05-01T22:39:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストから学習する患者表現の獲得（Learning Patient Representations from Text）</news:title>
   <news:publication_date>2026-05-01T22:39:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685548</loc>
  <lastmod>2026-05-01T22:39:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RiFCNによる高解像度リモートセンシング画像のセマンティックセグメンテーション（RiFCN: Recurrent Network in Fully Convolutional Network for Semantic Segmentation of High Resolution Remote Sensing Images）</news:title>
   <news:publication_date>2026-05-01T22:39:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685546</loc>
  <lastmod>2026-05-01T22:38:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPU上のニューラル機械翻訳におけるハイパーパラメータ最適化の探究（Exploring Hyper-Parameter Optimization for Neural Machine Translation on GPU Architectures）</news:title>
   <news:publication_date>2026-05-01T22:38:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685544</loc>
  <lastmod>2026-05-01T22:38:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cu酸化物高温超伝導体におけるサイト内磁気モーメントの向き（Orientation of the intra-unit-cell magnetic moment in the high-Tc superconductor HgBa2CuO4+δ）</news:title>
   <news:publication_date>2026-05-01T22:38:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685542</loc>
  <lastmod>2026-05-01T22:38:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環状・潜在変数・選択バイアスを同時に扱う制約ベース因果探索（A Constraint-Based Algorithm For Causal Discovery with Cycles, Latent Variables &amp;amp; Selection Bias）</news:title>
   <news:publication_date>2026-05-01T22:38:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685540</loc>
  <lastmod>2026-05-01T22:38:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2.5D格闘ゲームを学習する深層強化学習（DEEP REINFORCEMENT LEARNING FOR PLAYING 2.5D FIGHTING GAMES）</news:title>
   <news:publication_date>2026-05-01T22:38:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685538</loc>
  <lastmod>2026-05-01T22:37:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルフィー向け抽象化を学習する手法（Learning Selfie-Friendly Abstraction from Artistic Style Images）</news:title>
   <news:publication_date>2026-05-01T22:37:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685536</loc>
  <lastmod>2026-05-01T21:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アーティスト群要因の転移学習による音楽ジャンル分類（Transfer Learning of Artist Group Factors to Musical Genre Classification）</news:title>
   <news:publication_date>2026-05-01T21:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685534</loc>
  <lastmod>2026-05-01T21:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形態素的に豊かな入力の合成表現（Compositional Representation of Morphologically-Rich Input for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-01T21:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685532</loc>
  <lastmod>2026-05-01T21:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ位置推定の無監督学習による革新（Position Estimation of Camera Based on Unsupervised Learning）</news:title>
   <news:publication_date>2026-05-01T21:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685530</loc>
  <lastmod>2026-05-01T21:45:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックなインスタンス識別による教師なし特徴学習（Unsupervised Feature Learning via Non-Parametric Instance Discrimination）</news:title>
   <news:publication_date>2026-05-01T21:45:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685528</loc>
  <lastmod>2026-05-01T21:44:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮符号化分散計算の要点（Compressed Coded Distributed Computing）</news:title>
   <news:publication_date>2026-05-01T21:44:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685526</loc>
  <lastmod>2026-05-01T21:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アスペクト別感情分析の諸手法（Various Approaches to Aspect-based Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-01T21:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685524</loc>
  <lastmod>2026-05-01T21:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MTFH: 異種モダリティ検索を変える可変長ハッシュ学習（MTFH: A Matrix Tri-Factorization Hashing Framework for Efficient Cross-Modal Retrieval）</news:title>
   <news:publication_date>2026-05-01T21:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685522</loc>
  <lastmod>2026-05-01T20:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的で意思決定する複数主体の間の経路計画と深層強化学習（Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-01T20:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685520</loc>
  <lastmod>2026-05-01T20:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気象センサデータに基づく降水検出のデータ駆動型アプローチ (A DATA-DRIVEN APPROACH TO DETECTING PRECIPITATION FROM METEOROLOGICAL SENSOR DATA)</news:title>
   <news:publication_date>2026-05-01T20:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685518</loc>
  <lastmod>2026-05-01T20:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察からの行動模倣（Behavioral Cloning from Observation）</news:title>
   <news:publication_date>2026-05-01T20:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685516</loc>
  <lastmod>2026-05-01T20:50:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超伝導オプトエレクトロニックニューロンの可塑性（Superconducting Optoelectronic Neurons III: Synaptic Plasticity）</news:title>
   <news:publication_date>2026-05-01T20:50:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685514</loc>
  <lastmod>2026-05-01T20:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>風からより多くを得る：ベッツの法則を複数タービンへ拡張する（Getting More Out of the Wind: Extending Betz’s Law to Multiple Turbines）</news:title>
   <news:publication_date>2026-05-01T20:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685512</loc>
  <lastmod>2026-05-01T20:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗闇で見る技術の進化（Learning to See in the Dark）</news:title>
   <news:publication_date>2026-05-01T20:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685510</loc>
  <lastmod>2026-05-01T20:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重みプルーニングによる正則化効果の強化（ENHANCING THE REGULARIZATION EFFECT OF WEIGHT PRUNING IN ARTIFICIAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-01T20:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685508</loc>
  <lastmod>2026-05-01T19:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸・非滑らかな確率的近似の解析（Analysis of nonsmooth stochastic approximation: the differential inclusion approach）</news:title>
   <news:publication_date>2026-05-01T19:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685506</loc>
  <lastmod>2026-05-01T19:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索のための分布強化学習（Exploration by Distributional Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-01T19:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685504</loc>
  <lastmod>2026-05-01T19:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラレンズのMTFを自動推定する方法（Automatic Estimation of Modulation Transfer Functions）</news:title>
   <news:publication_date>2026-05-01T19:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685502</loc>
  <lastmod>2026-05-01T19:55:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測定されない交絡がある場合のアルゴリズム的意思決定（Algorithmic Decision Making in the Presence of Unmeasured Confounding）</news:title>
   <news:publication_date>2026-05-01T19:55:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685500</loc>
  <lastmod>2026-05-01T19:55:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LASSOのハイパーパラメータ選択におけるヘッジ手法の提案（Hedging parameter selection for basis pursuit）</news:title>
   <news:publication_date>2026-05-01T19:55:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685498</loc>
  <lastmod>2026-05-01T19:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑微細組織の高スループット定量計測に深層学習を使う（High throughput quantitative metallography for complex microstructures using deep learning）</news:title>
   <news:publication_date>2026-05-01T19:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685496</loc>
  <lastmod>2026-05-01T19:54:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選好学習のベイズ型能動学習と深いガウス過程（Bayesian active learning for choice models with deep Gaussian processes）</news:title>
   <news:publication_date>2026-05-01T19:54:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685494</loc>
  <lastmod>2026-05-01T19:03:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシングと機械学習でデング熱媒介蚊の発生を予測する（Modeling Dengue Vector Population Using Remotely Sensed Data and Machine Learning）</news:title>
   <news:publication_date>2026-05-01T19:03:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685492</loc>
  <lastmod>2026-05-01T19:03:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L2-Boostingにおける選択的推論の実践と意義（Selective Inference for L2-Boosting）</news:title>
   <news:publication_date>2026-05-01T19:03:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685490</loc>
  <lastmod>2026-05-01T19:01:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ログ正規混合モデルによる学習オンライン行動の時間推定（Time-on-Task Estimation with Log-Normal Mixture Model）</news:title>
   <news:publication_date>2026-05-01T19:01:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685488</loc>
  <lastmod>2026-05-01T19:00:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNデータフローの再利用性・性能・ハードウェアコストの理解（Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach Using MAESTRO）</news:title>
   <news:publication_date>2026-05-01T19:00:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685486</loc>
  <lastmod>2026-05-01T19:00:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オブジェクトとテキスト誘導セマンティクスによるCNNベースの活動認識（OBJECT AND TEXT-GUIDED SEMANTICS FOR CNN-BASED ACTIVITY RECOGNITION）</news:title>
   <news:publication_date>2026-05-01T19:00:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685484</loc>
  <lastmod>2026-05-01T18:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転自動化における失敗予測（Failure Prediction for Autonomous Driving）</news:title>
   <news:publication_date>2026-05-01T18:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685482</loc>
  <lastmod>2026-05-01T18:08:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯端末上での深層学習による作物病害監視の検証（Assessing a mobile-based deep learning model for plant disease surveillance）</news:title>
   <news:publication_date>2026-05-01T18:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685480</loc>
  <lastmod>2026-05-01T18:07:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像における概念検出のための教師なし学習比較（Unsupervised learning for concept detection in medical images: a comparative analysis）</news:title>
   <news:publication_date>2026-05-01T18:07:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685478</loc>
  <lastmod>2026-05-01T18:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DISCUS：小型キューブサットで小惑星の内部を探る（DISCUS - The Deep Interior Scanning CubeSat mission to a rubble pile near-Earth asteroid）</news:title>
   <news:publication_date>2026-05-01T18:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685476</loc>
  <lastmod>2026-05-01T18:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模機械学習における動的制御フローの実装と意義（Dynamic Control Flow in Large-Scale Machine Learning）</news:title>
   <news:publication_date>2026-05-01T18:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685474</loc>
  <lastmod>2026-05-01T18:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グレイ機械学習の導入と要点（A brief introduction to the Grey Machine Learning）</news:title>
   <news:publication_date>2026-05-01T18:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685472</loc>
  <lastmod>2026-05-01T17:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化シアミーズネットワークによる特徴抽出と病変スクリーニングへの応用（Feature extraction with regularized siamese networks for outlier detection: application to lesion screening in medical imaging）</news:title>
   <news:publication_date>2026-05-01T17:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685470</loc>
  <lastmod>2026-05-01T17:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列をクラスタリングするための量子力学的手法（Using Quantum Mechanics to Cluster Time Series）</news:title>
   <news:publication_date>2026-05-01T17:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685468</loc>
  <lastmod>2026-05-01T17:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多コアプロセッサ上での深層学習性能チューニング（Performance tuning for deep learning on a many-core processor）</news:title>
   <news:publication_date>2026-05-01T17:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685466</loc>
  <lastmod>2026-05-01T17:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳内エラー検出における深層学習（Intracranial Error Detection via Deep Learning）</news:title>
   <news:publication_date>2026-05-01T17:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685464</loc>
  <lastmod>2026-05-01T17:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続かつ可分な報酬関数を持つ組合せ純粋探索とその応用（Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications）</news:title>
   <news:publication_date>2026-05-01T17:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685462</loc>
  <lastmod>2026-05-01T17:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クリック率を超えて：多段階フィードバックを考慮したウェブリンク選択（Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback）</news:title>
   <news:publication_date>2026-05-01T17:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685460</loc>
  <lastmod>2026-05-01T17:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られたデータからの画像生成のためのGAN移転（Transferring GANs: generating images from limited data）</news:title>
   <news:publication_date>2026-05-01T17:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685458</loc>
  <lastmod>2026-05-01T16:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGAで実現するハードウェア対応リザバーコンピューティングの効率設計（Efficient Design of Hardware-Enabled Reservoir Computing in FPGAs）</news:title>
   <news:publication_date>2026-05-01T16:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685456</loc>
  <lastmod>2026-05-01T16:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IntelCaffeによる8ビット低精度推論の実装と評価（Highly Efficient 8-bit Low Precision Inference of Convolutional Neural Networks with IntelCaffe）</news:title>
   <news:publication_date>2026-05-01T16:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685454</loc>
  <lastmod>2026-05-01T16:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化深層ニューラルネットワークにおける累乗則の観察（Power Law in Sparsified Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-01T16:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685452</loc>
  <lastmod>2026-05-01T16:05:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Langevin Monte Carloの非凸設定における収束速度（Convergence Rates for Langevin Monte Carlo in the Nonconvex Setting）</news:title>
   <news:publication_date>2026-05-01T16:05:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685450</loc>
  <lastmod>2026-05-01T16:04:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分線形データ領域における学習可能性の推定 (Estimating Learnability in the Sublinear Data Regime)</news:title>
   <news:publication_date>2026-05-01T16:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685448</loc>
  <lastmod>2026-05-01T16:04:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的マルチアームバンディットへの情報幾何学的アプローチ（BelMan: An Information-Geometric Approach to Stochastic Bandits）</news:title>
   <news:publication_date>2026-05-01T16:04:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685446</loc>
  <lastmod>2026-05-01T16:04:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布適応型回帰の実務的意義（Distribution Assertive Regression）</news:title>
   <news:publication_date>2026-05-01T16:04:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685444</loc>
  <lastmod>2026-05-01T15:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェネリック自律進化型ニューラルファジー制御器による高性能ヘキサコプター高度制御（A Generic Self-Evolving Neuro-Fuzzy Controller based High-performance Hexacopter Altitude Control System）</news:title>
   <news:publication_date>2026-05-01T15:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685442</loc>
  <lastmod>2026-05-01T15:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データから生物学的因果を問う：ベイジアンネットワークによる小規模ネットワークの実証研究（Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks）</news:title>
   <news:publication_date>2026-05-01T15:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685440</loc>
  <lastmod>2026-05-01T15:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語ラディカルを組み込んだニューラル機械翻訳（Incorporating Chinese Radicals Into Neural Machine Translation: Deeper Than Character Level）</news:title>
   <news:publication_date>2026-05-01T15:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685438</loc>
  <lastmod>2026-05-01T15:09:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>pytrec_eval の実務的意義と速さの源泉（Pytrec_eval: An Extremely Fast Python Interface to trec_eval）</news:title>
   <news:publication_date>2026-05-01T15:09:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685436</loc>
  <lastmod>2026-05-01T15:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヨーロッパにおける人類集団の進化史（The evolutionary history of human populations in Europe）</news:title>
   <news:publication_date>2026-05-01T15:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685434</loc>
  <lastmod>2026-05-01T15:08:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコンの一般目的原子間ポテンシャルを機械学習で構築（Machine learning a general purpose interatomic potential for silicon）</news:title>
   <news:publication_date>2026-05-01T15:08:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685432</loc>
  <lastmod>2026-05-01T15:08:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所角度に基づく次元推定（Local Angles and Dimension Estimation from Data on Manifolds）</news:title>
   <news:publication_date>2026-05-01T15:08:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685430</loc>
  <lastmod>2026-05-01T14:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画素単位の注意機構による動的推論（Pixel-wise Attentional Gating for Scene Parsing）</news:title>
   <news:publication_date>2026-05-01T14:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685428</loc>
  <lastmod>2026-05-01T14:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型LSTMと教師付きアテンションによるメール詐欺検知（A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing）</news:title>
   <news:publication_date>2026-05-01T14:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685426</loc>
  <lastmod>2026-05-01T14:16:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的多様体上の辞書学習とスパース符号化（Dictionary Learning and Sparse Coding on Statistical Manifolds）</news:title>
   <news:publication_date>2026-05-01T14:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685424</loc>
  <lastmod>2026-05-01T14:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的予測と強化学習で人手を減らす翻訳学習（A Reinforcement Learning Approach to Interactive-Predictive Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-01T14:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685422</loc>
  <lastmod>2026-05-01T14:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復解の収束性に関するミラーディセント法の解析（Convergence of the Iterates in Mirror Descent Methods）</news:title>
   <news:publication_date>2026-05-01T14:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685420</loc>
  <lastmod>2026-05-01T14:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>持ち上げ型ニューラルネットワーク（Lifted Neural Networks）</news:title>
   <news:publication_date>2026-05-01T14:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685418</loc>
  <lastmod>2026-05-01T14:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語理解機能の高速かつ大規模な拡張（Fast and Scalable Expansion of Natural Language Understanding Functionality for Intelligent Agents）</news:title>
   <news:publication_date>2026-05-01T14:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685416</loc>
  <lastmod>2026-05-01T13:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ln(1/x) 再合成の重要性：HERAデータの新しいQCD解析（The importance of ln(1/x) resummation: a new QCD analysis of HERA data）</news:title>
   <news:publication_date>2026-05-01T13:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685414</loc>
  <lastmod>2026-05-01T13:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの深さはどこまで必要か（How deep should be the depth of convolutional neural networks: a backyard dog case study）</news:title>
   <news:publication_date>2026-05-01T13:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685412</loc>
  <lastmod>2026-05-01T13:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情認識のためのトランスフォーマー（Transformer for Emotion Recognition）</news:title>
   <news:publication_date>2026-05-01T13:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685410</loc>
  <lastmod>2026-05-01T13:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接続部分グラフで頑健に埋めるノード表現（RECS: Robust Graph Embedding Using Connection Subgraphs）</news:title>
   <news:publication_date>2026-05-01T13:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685408</loc>
  <lastmod>2026-05-01T13:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RMDL：ランダム・マルチモデル深層学習による分類（RMDL: Random Multimodel Deep Learning for Classification）</news:title>
   <news:publication_date>2026-05-01T13:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685406</loc>
  <lastmod>2026-05-01T13:18:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NoisinによるRNNの偏りのない正則化（Noisin: Unbiased Regularization for Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-01T13:18:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685404</loc>
  <lastmod>2026-05-01T13:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルベースの予測可能で解釈可能なノード埋め込み (t-PINE: Tensor-based Predictable and Interpretable Node Embeddings)</news:title>
   <news:publication_date>2026-05-01T13:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685402</loc>
  <lastmod>2026-05-01T12:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホットジュピターのシリケートとチタン雲の形成（FORMATION OF SILICATE AND TITANIUM CLOUDS ON HOT JUPITERS）</news:title>
   <news:publication_date>2026-05-01T12:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685400</loc>
  <lastmod>2026-05-01T12:25:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔表情から感情の次元を推定する多成分CNN-RNN（A Multi-component CNN-RNN Approach for Dimensional Emotion Recognition in-the-wild）</news:title>
   <news:publication_date>2026-05-01T12:25:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685398</loc>
  <lastmod>2026-05-01T12:24:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Seq注意モデルにおける言語的一般化と失敗の境界（The Fine Line between Linguistic Generalization and Failure in Seq2Seq-Attention Models）</news:title>
   <news:publication_date>2026-05-01T12:24:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685396</loc>
  <lastmod>2026-05-01T12:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元的感情認識における視覚・テキスト情報の統合（Dimensional emotion recognition using visual and textual cues）</news:title>
   <news:publication_date>2026-05-01T12:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685394</loc>
  <lastmod>2026-05-01T12:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存巡回セールスマン問題の最適化手法と学習を巡る分析（Cuts, Primal Heuristics, and Learning to Branch for the Time-Dependent Traveling Salesman Problem）</news:title>
   <news:publication_date>2026-05-01T12:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685392</loc>
  <lastmod>2026-05-01T12:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siameseネットワークを用いた敵対的事例生成（Siamese networks for generating adversarial examples）</news:title>
   <news:publication_date>2026-05-01T12:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685390</loc>
  <lastmod>2026-05-01T12:23:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InceptB: 伝統的ベンガル遊戯認識のためのCNNベース分類手法 (InceptB: A CNN Based Classification Approach for Recognizing Traditional Bengali Games)</news:title>
   <news:publication_date>2026-05-01T12:23:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685388</loc>
  <lastmod>2026-05-01T11:31:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>本物の天文学研究体験が教師に与えた主要な成果（Major Outcomes of an Authentic Astronomy Research Experience）</news:title>
   <news:publication_date>2026-05-01T11:31:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685386</loc>
  <lastmod>2026-05-01T11:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイタン南極成層圏雲におけるベンゼン氷の検出（Study of Titan’s fall southern stratospheric polar cloud composition with Cassini/CIRS: detection of benzene ice）</news:title>
   <news:publication_date>2026-05-01T11:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685384</loc>
  <lastmod>2026-05-01T11:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移民を含む人口の平衡方程式（Equilibrium Equations for Human Populations with Immigration）</news:title>
   <news:publication_date>2026-05-01T11:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685382</loc>
  <lastmod>2026-05-01T11:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトルデータを用いた水質パラメータ推定（MACHINE LEARNING REGRESSION ON HYPERSPECTRAL DATA TO ESTIMATE MULTIPLE WATER PARAMETERS）</news:title>
   <news:publication_date>2026-05-01T11:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685380</loc>
  <lastmod>2026-05-01T11:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF-PUFによるIoT端末認証の革新（RF-PUF: Enhancing IoT Security through Authentication of Wireless Nodes using In-situ Machine Learning）</news:title>
   <news:publication_date>2026-05-01T11:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685378</loc>
  <lastmod>2026-05-01T11:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在ドメイン発見によるドメイン適応の強化（Boosting Domain Adaptation by Discovering Latent Domains）</news:title>
   <news:publication_date>2026-05-01T11:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685376</loc>
  <lastmod>2026-05-01T11:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木探索アルゴリズムのオープンループ実行（Open Loop Execution of Tree-Search Algorithms）</news:title>
   <news:publication_date>2026-05-01T11:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685374</loc>
  <lastmod>2026-05-01T10:27:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティの重要度を学ぶカーネルモデル（Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling）</news:title>
   <news:publication_date>2026-05-01T10:27:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685372</loc>
  <lastmod>2026-05-01T10:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連邦学生ローン返済に影響する要因のデータ駆動探索（Data-Driven Exploration of Factors Affecting Federal Student Loan Repayment）</news:title>
   <news:publication_date>2026-05-01T10:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685370</loc>
  <lastmod>2026-05-01T10:20:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ列の異常・変化検出を曲率一定の多様体埋め込みで行う意義（Anomaly and Change Detection in Graph Streams through Constant-Curvature Manifold Embeddings）</news:title>
   <news:publication_date>2026-05-01T10:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685368</loc>
  <lastmod>2026-05-01T10:19:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限の特徴点で十分な対応点を得る検出法（SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning）</news:title>
   <news:publication_date>2026-05-01T10:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685366</loc>
  <lastmod>2026-05-01T10:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>iベクトルベースのロバスト話者認識のための深い判別分析（Deep Discriminant Analysis for i-vector Based Robust Speaker Recognition）</news:title>
   <news:publication_date>2026-05-01T10:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685364</loc>
  <lastmod>2026-05-01T10:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dプリント部品の非破壊検査を高感度化する非同期ロックインサーモグラフィ（Asynchronous Lock-In Thermography of 3D Printed PLA and ABS samples）</news:title>
   <news:publication_date>2026-05-01T10:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685362</loc>
  <lastmod>2026-05-01T10:18:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織病理画像の特徴抽出比較：LBP、HOG、深層特徴の実践的示唆（Comparing LBP, HOG and Deep Features for Classification of Histopathology Images）</news:title>
   <news:publication_date>2026-05-01T10:18:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685360</loc>
  <lastmod>2026-05-01T09:26:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習から学ぶこと — ボットネット攻撃における機械学習の能力と限界 (What we learn from learning - Understanding capabilities and limitations of machine learning in botnet attacks)</news:title>
   <news:publication_date>2026-05-01T09:26:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685358</loc>
  <lastmod>2026-05-01T09:25:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの深度推定手法の評価指標整備（Evaluation of CNN-based Single-Image Depth Estimation Methods）</news:title>
   <news:publication_date>2026-05-01T09:25:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685356</loc>
  <lastmod>2026-05-01T09:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のランドマーク局所化を深堀りする（Facial Landmark Point Localization using Coarse-to-Fine Deep Recurrent Neural Network）</news:title>
   <news:publication_date>2026-05-01T09:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685354</loc>
  <lastmod>2026-05-01T09:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音分散制約を持つLMATアルゴリズムの概要（Noise constrained least mean absolute third algorithm）</news:title>
   <news:publication_date>2026-05-01T09:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685352</loc>
  <lastmod>2026-05-01T09:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習によるカスケードCNNでの顔属性分類（Multi-task Learning of Cascaded CNN for Facial Attribute Classification）</news:title>
   <news:publication_date>2026-05-01T09:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685350</loc>
  <lastmod>2026-05-01T09:23:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な伝播現象を論理的に学習する——複数インスタンス学習に基づく前位相空間の獲得（Learning Pretopological Spaces to Model Complex Propagation Phenomena: A Multiple Instance Learning Approach Based on a Logical Modeling）</news:title>
   <news:publication_date>2026-05-01T09:23:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685348</loc>
  <lastmod>2026-05-01T09:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔属性分類におけるラベル不足を解決する深層マルチラベル転移ネットワーク（Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification）</news:title>
   <news:publication_date>2026-05-01T09:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685346</loc>
  <lastmod>2026-05-01T08:31:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習に基づく圧縮MRIの設計（Learning-Based Compressive MRI）</news:title>
   <news:publication_date>2026-05-01T08:31:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685344</loc>
  <lastmod>2026-05-01T08:31:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互関連する概念の概念空間表現の学習（Learning Conceptual Space Representations of Interrelated Concepts）</news:title>
   <news:publication_date>2026-05-01T08:31:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685342</loc>
  <lastmod>2026-05-01T08:30:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼブラフィッシュの前視蓋ニューロンは疎な符号化で説明できる（Sparse Coding Predicts Optic Flow Specificities of Zebrafish Pretectal Neurons）</news:title>
   <news:publication_date>2026-05-01T08:30:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685340</loc>
  <lastmod>2026-05-01T08:29:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間動画から感情を読む技術と実務への示唆（audEERING’s approach to the One-Minute-Gradual Emotion Challenge）</news:title>
   <news:publication_date>2026-05-01T08:29:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685338</loc>
  <lastmod>2026-05-01T08:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のバンディットフィードバックから学ぶニューラル意味解析器の改良（Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback）</news:title>
   <news:publication_date>2026-05-01T08:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685336</loc>
  <lastmod>2026-05-01T08:29:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デスクトップ資源のディープリンク（Deep Linking Desktop Resources）</news:title>
   <news:publication_date>2026-05-01T08:29:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685334</loc>
  <lastmod>2026-05-01T08:29:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き多腕バンディット問題の漸近最適戦略（An Asymptotically Optimal Strategy for Constrained Multi-armed Bandit Problems）</news:title>
   <news:publication_date>2026-05-01T08:29:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685332</loc>
  <lastmod>2026-05-01T07:37:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>mFISH画像のセマンティックセグメンテーション（Semantic segmentation of mFISH images using convolutional networks）</news:title>
   <news:publication_date>2026-05-01T07:37:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685330</loc>
  <lastmod>2026-05-01T07:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン利用規約の不当条項を自動検出するCLAUDETTE（CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service）</news:title>
   <news:publication_date>2026-05-01T07:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685328</loc>
  <lastmod>2026-05-01T07:34:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FOUND GRAPH DATA AND PLANTED VERTEX COVERS（FOUND GRAPH DATA AND PLANTED VERTEX COVERS）</news:title>
   <news:publication_date>2026-05-01T07:34:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685326</loc>
  <lastmod>2026-05-01T07:34:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一チャネル盲音源分離による歌声検出の比較研究（Single-Channel Blind Source Separation for Singing Voice Detection）</news:title>
   <news:publication_date>2026-05-01T07:34:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685324</loc>
  <lastmod>2026-05-01T07:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補聴器向け深層ノイズ抑圧の実装と評価（DEEP DENOISING FOR HEARING AID APPLICATIONS）</news:title>
   <news:publication_date>2026-05-01T07:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685322</loc>
  <lastmod>2026-05-01T06:42:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中プロトンの運動量分布の異方性（The Anisotropy of the Proton Momentum Distribution in Water）</news:title>
   <news:publication_date>2026-05-01T06:42:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685320</loc>
  <lastmod>2026-05-01T06:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザーがHPCジョブを中止する理由（Why do Users Kill HPC Jobs?）</news:title>
   <news:publication_date>2026-05-01T06:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685318</loc>
  <lastmod>2026-05-01T06:41:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力系統リスク評価の計算予算最適化（Optimization of computational budget for power system risk assessment）</news:title>
   <news:publication_date>2026-05-01T06:41:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685316</loc>
  <lastmod>2026-05-01T06:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SafeRNetによる安全経路計算の提案（SafeRNet: Safe Transportation Routing in the era of Internet of Vehicles and Mobile Crowd Sensing）</news:title>
   <news:publication_date>2026-05-01T06:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685314</loc>
  <lastmod>2026-05-01T06:39:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力網における迅速な危険度ランキング手法の提案（Anticipating contingengies in power grids using fast neural net screening）</news:title>
   <news:publication_date>2026-05-01T06:39:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685312</loc>
  <lastmod>2026-05-01T06:39:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理デバイスのデータ駆動推定（Data-Driven Inference of Physical Devices: Theory and Implementation）</news:title>
   <news:publication_date>2026-05-01T06:39:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685310</loc>
  <lastmod>2026-05-01T06:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフベイズ最適化（Graph Bayesian Optimization: Algorithms, Evaluations and Applications）</news:title>
   <news:publication_date>2026-05-01T06:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685308</loc>
  <lastmod>2026-05-01T05:47:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期化問題における視覚的物体追跡（Visual Object Tracking: The Initialisation Problem）</news:title>
   <news:publication_date>2026-05-01T05:47:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685306</loc>
  <lastmod>2026-05-01T05:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経進化の可視化ツール VINE（VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution）</news:title>
   <news:publication_date>2026-05-01T05:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685304</loc>
  <lastmod>2026-05-01T05:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの皮肉（アイロニー）を分解して読む――依存構文解析とDeepMojiを組み合わせた手法（Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection）</news:title>
   <news:publication_date>2026-05-01T05:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685302</loc>
  <lastmod>2026-05-01T05:45:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索行動からパーキンソン病を検出する試み（Detecting Parkinson’s Disease from interactions with a search engine: Is expert knowledge sufficient?）</news:title>
   <news:publication_date>2026-05-01T05:45:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685300</loc>
  <lastmod>2026-05-01T05:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカルクリティック訓練による深層ニューラルネットワークの分解的学習（Local Critic Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-01T05:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685298</loc>
  <lastmod>2026-05-01T05:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顧客特徴量を用いた非パラメトリック価格分析（Nonparametric Pricing Analytics with Customer Covariates）</news:title>
   <news:publication_date>2026-05-01T05:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685296</loc>
  <lastmod>2026-05-01T04:52:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー固有の美的ランキング枠組みが示す実務的意義（USAR: an Interactive User-specific Aesthetic Ranking Framework for Images）</news:title>
   <news:publication_date>2026-05-01T04:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685294</loc>
  <lastmod>2026-05-01T04:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6種の藻類を自動識別する可能性（The feasibility of automated identification of six algae types using neural networks and fluorescence-based spectral-morphological features）</news:title>
   <news:publication_date>2026-05-01T04:52:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685292</loc>
  <lastmod>2026-05-01T04:52:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特性ソート型ファクターモデルにおける深層学習の応用（Deep Learning in Characteristics-Sorted Factor Models）</news:title>
   <news:publication_date>2026-05-01T04:52:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685290</loc>
  <lastmod>2026-05-01T04:51:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚最適化GANによる単一画像デハイジング（Perceptually Optimized Generative Adversarial Network for Single Image Dehazing）</news:title>
   <news:publication_date>2026-05-01T04:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685288</loc>
  <lastmod>2026-05-01T04:50:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミング映像における未知異常検出とエネルギーベース生成モデル（Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models）</news:title>
   <news:publication_date>2026-05-01T04:50:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685286</loc>
  <lastmod>2026-05-01T04:50:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト要約と感情分類を同時に改善する階層的エンドツーエンドモデル（A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification）</news:title>
   <news:publication_date>2026-05-01T04:50:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685284</loc>
  <lastmod>2026-05-01T04:50:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stack-Pointer Networksによる依存構文解析の革新（Stack-Pointer Networks for Dependency Parsing）</news:title>
   <news:publication_date>2026-05-01T04:50:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685282</loc>
  <lastmod>2026-05-01T03:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおける数値精度の探究 (EXPLORATION OF NUMERICAL PRECISION IN DEEP NEURAL NETWORKS)</news:title>
   <news:publication_date>2026-05-01T03:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685280</loc>
  <lastmod>2026-05-01T03:50:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された地震位相検出（Generalized Seismic Phase Detection with Deep Learning）</news:title>
   <news:publication_date>2026-05-01T03:50:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685278</loc>
  <lastmod>2026-05-01T03:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KKT写像の強い計量（部分）正則性とPLQ凸合成最適化（STRONG METRIC (SUB)REGULARITY OF KKT MAPPINGS FOR PIECEWISE LINEAR-QUADRATIC CONVEX-COMPOSITE OPTIMIZATION）</news:title>
   <news:publication_date>2026-05-01T03:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685276</loc>
  <lastmod>2026-05-01T03:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール画素単位ディープ畳み込みニューラルネットワークによる自動構造物損傷検出（Multi-scale Pixel-wise Deep Convolutional Neural Networks for Automated Damage Detection）</news:title>
   <news:publication_date>2026-05-01T03:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685274</loc>
  <lastmod>2026-05-01T03:48:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床ノートから自動で新生児黄疸を符号化する手法（Automatic Coding for Neonatal Jaundice From Free Text Data Using Ensemble Methods）</news:title>
   <news:publication_date>2026-05-01T03:48:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685272</loc>
  <lastmod>2026-05-01T03:47:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均場解析によるニューラルネットの大数の法則（Mean Field Analysis of Neural Networks: A Law of Large Numbers）</news:title>
   <news:publication_date>2026-05-01T03:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685270</loc>
  <lastmod>2026-05-01T02:56:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な教師なし深層表現学習による脳構造解析（Large-Scale Unsupervised Deep Representation Learning for Brain Structure）</news:title>
   <news:publication_date>2026-05-01T02:56:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685268</loc>
  <lastmod>2026-05-01T02:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF信号を用いたIoT端末の本人認証技術（RF-PUF: IoT Security Enhancement through Authentication of Wireless Nodes using In-situ Machine Learning）</news:title>
   <news:publication_date>2026-05-01T02:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685266</loc>
  <lastmod>2026-05-01T02:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EML-NETによるサリエンシー予測の拡張可能な多層ネットワーク（EML-NET: An Expandable Multi-Layer NETwork for Saliency Prediction）</news:title>
   <news:publication_date>2026-05-01T02:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685264</loc>
  <lastmod>2026-05-01T02:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BLAZEITによる動画解析の効率化（BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics）</news:title>
   <news:publication_date>2026-05-01T02:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685262</loc>
  <lastmod>2026-05-01T02:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常性を捉えるEEG向け適応型アンサンブル学習（Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface）</news:title>
   <news:publication_date>2026-05-01T02:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685260</loc>
  <lastmod>2026-05-01T02:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Alpha-Betaダイバージェンスによる変分推論の拡張（Alpha-Beta Divergence For Variational Inference）</news:title>
   <news:publication_date>2026-05-01T02:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685258</loc>
  <lastmod>2026-05-01T02:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声における感情認識を支える半教師あり生成モデルの提案（OMG Emotion Challenge - ExCouple Team）</news:title>
   <news:publication_date>2026-05-01T02:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685256</loc>
  <lastmod>2026-05-01T02:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済みCNNと連想記憶バンクを用いた教師なし学習（Unsupervised Learning using Pretrained CNN and Associative Memory Bank）</news:title>
   <news:publication_date>2026-05-01T02:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685254</loc>
  <lastmod>2026-05-01T02:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>姿勢推定のためのCNN損失と勾配をリーマン幾何で定式化する（Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry）</news:title>
   <news:publication_date>2026-05-01T02:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685252</loc>
  <lastmod>2026-05-01T01:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度な表情解析と次元感情モデル（Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model）</news:title>
   <news:publication_date>2026-05-01T01:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685250</loc>
  <lastmod>2026-05-01T01:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-SVRG: 大規模最適化のための分散誤差低減（k-SVRG: Variance Reduction for Large Scale Optimization）</news:title>
   <news:publication_date>2026-05-01T01:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685248</loc>
  <lastmod>2026-05-01T01:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X-CNNのクロスモーダルトポロジーの自動推論（Automatic Inference of Cross-modal Connection Topologies for X-CNNs）</news:title>
   <news:publication_date>2026-05-01T01:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685246</loc>
  <lastmod>2026-05-01T01:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律走行車の安全性を強化する敵対的深層強化学習（Robust Deep Reinforcement Learning for Security and Safety in Autonomous Vehicle Systems）</news:title>
   <news:publication_date>2026-05-01T01:58:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685244</loc>
  <lastmod>2026-05-01T01:57:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期電力価格予測における古典的モデルと非線形モデルの比較（Comparison of Classical and Nonlinear Models for Short-Term Electricity Price Prediction）</news:title>
   <news:publication_date>2026-05-01T01:57:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685242</loc>
  <lastmod>2026-05-01T01:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習速度を教師にする半教師あり学習（SaaS: Speed as a Supervisor for Semi-supervised Learning）</news:title>
   <news:publication_date>2026-05-01T01:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685240</loc>
  <lastmod>2026-05-01T01:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>modAL：Pythonのためのモジュール式能動学習フレームワーク (modAL: A modular active learning framework for Python)</news:title>
   <news:publication_date>2026-05-01T01:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685238</loc>
  <lastmod>2026-05-01T01:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地上設置ライダーによる雲検出に対する全畳み込みネットワークの適用（Lidar Cloud Detection with Fully Convolutional Networks）</news:title>
   <news:publication_date>2026-05-01T01:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685236</loc>
  <lastmod>2026-05-01T01:02:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模離散時間生存モデルによるニューラルネットワークの適用（A Scalable Discrete-Time Survival Model for Neural Networks）</news:title>
   <news:publication_date>2026-05-01T01:02:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685234</loc>
  <lastmod>2026-05-01T01:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ解像度・マルチモーダルセンサ融合とラベル不確かさの扱い（Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty）</news:title>
   <news:publication_date>2026-05-01T01:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685232</loc>
  <lastmod>2026-05-01T01:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な弱教師あり事前学習の限界を探る（Exploring the Limits of Weakly Supervised Pretraining）</news:title>
   <news:publication_date>2026-05-01T01:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685230</loc>
  <lastmod>2026-05-01T00:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの訓練可能性と精度を粒子系として考える（TRAINABILITY AND ACCURACY OF NEURAL NETWORKS: AN INTERACTING PARTICLE SYSTEM APPROACH）</news:title>
   <news:publication_date>2026-05-01T00:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685228</loc>
  <lastmod>2026-05-01T00:09:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Glow: ニューラルネットワーク向けグラフローワーコンパイラの要点（Glow: Graph Lowering Compiler Techniques for Neural Networks）</news:title>
   <news:publication_date>2026-05-01T00:09:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685226</loc>
  <lastmod>2026-05-01T00:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似Temporal Difference学習は可逆ポリシー下で勾配降下になる（Approximate Temporal Difference Learning is a Gradient Descent for Reversible Policies）</news:title>
   <news:publication_date>2026-05-01T00:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685224</loc>
  <lastmod>2026-05-01T00:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改善したDRNを用いる交通流予測の動的モデル（A Dynamic Model for Traffic Flow Prediction Using Improved DRN）</news:title>
   <news:publication_date>2026-05-01T00:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685222</loc>
  <lastmod>2026-05-01T00:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>料理画像とレシピの大規模検索技術（Images &amp;amp; Recipes: Retrieval in the cooking context）</news:title>
   <news:publication_date>2026-05-01T00:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685220</loc>
  <lastmod>2026-05-01T00:07:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペイン観光需要の予測における機械学習の有効性（MODELLING TOURISM DEMAND TO SPAIN WITH MACHINE LEARNING TECHNIQUES. THE IMPACT OF FORECAST HORIZON ON MODEL SELECTION）</news:title>
   <news:publication_date>2026-05-01T00:07:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685218</loc>
  <lastmod>2026-04-30T23:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック循環・非循環グラフにおけるスペクトルクラスタリング（Spectral clustering algorithms for the detection of clusters in block-cyclic and block-acyclic graphs）</news:title>
   <news:publication_date>2026-04-30T23:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685216</loc>
  <lastmod>2026-04-30T23:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対ネットワークで実現する高速かつ高精度な検出器シミュレーション（Fast and accurate simulation of particle detectors using generative adversarial networks）</news:title>
   <news:publication_date>2026-04-30T23:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685214</loc>
  <lastmod>2026-04-30T23:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペイン地域観光市場の相互依存性をモデル化する手法（Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model）</news:title>
   <news:publication_date>2026-04-30T23:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685212</loc>
  <lastmod>2026-04-30T23:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔と声を同じ座標で比較する技術の衝撃（Learnable PINs: Cross-Modal Embeddings for Person Identity）</news:title>
   <news:publication_date>2026-04-30T23:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685210</loc>
  <lastmod>2026-04-30T23:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索行動から学習効果を予測する（Predicting User Knowledge Gain in Informational Search Sessions）</news:title>
   <news:publication_date>2026-04-30T23:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685208</loc>
  <lastmod>2026-04-30T23:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒状堆積床の収縮・クリープとアーミング（Granular bed consolidation, creep and armoring under subcritical fluid flow）</news:title>
   <news:publication_date>2026-04-30T23:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685206</loc>
  <lastmod>2026-04-30T23:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データに対する分類と外れ値検出アルゴリズムの評価（An Evaluation of Classification and Outlier Detection Algorithms）</news:title>
   <news:publication_date>2026-04-30T23:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685204</loc>
  <lastmod>2026-04-30T22:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な問いに答える技術：質問の側面（ファセット）を見極める（Characterizing Question Facets for Complex Answer Retrieval）</news:title>
   <news:publication_date>2026-04-30T22:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685202</loc>
  <lastmod>2026-04-30T22:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COBRASTSによる時系列の半教師ありクラスタリング（COBRASTS: A new approach to Semi-Supervised Clustering of Time Series）</news:title>
   <news:publication_date>2026-04-30T22:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685200</loc>
  <lastmod>2026-04-30T22:09:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁場を持つ鼓動するB型星HD 43317の前方地震学的モデリング（Forward seismic modelling of the pulsating magnetic B-type star HD 43317）</news:title>
   <news:publication_date>2026-04-30T22:09:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685198</loc>
  <lastmod>2026-04-30T22:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖ニューラルネットワーク（Markov Chain Neural Networks）</news:title>
   <news:publication_date>2026-04-30T22:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685196</loc>
  <lastmod>2026-04-30T22:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Chineseピンイン誤入力補正のための知識統合型ニューラル機械翻訳（Knowledge and Neural Machine Translation Powered Chinese Pinyin Typo Correction）</news:title>
   <news:publication_date>2026-04-30T22:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685194</loc>
  <lastmod>2026-04-30T22:07:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知ロボットにおける深層ニューラルネットワークの可能性と限界（Potentials and Limitations of Deep Neural Networks for Cognitive Robots）</news:title>
   <news:publication_date>2026-04-30T22:07:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685192</loc>
  <lastmod>2026-04-30T22:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット支援手術における動作とタスクの同時分類（Joint Surgical Gesture and Task Classification with Multi-Task and Multimodal Learning）</news:title>
   <news:publication_date>2026-04-30T22:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685190</loc>
  <lastmod>2026-04-30T21:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNとグラフを用いた半教師あり学習による危機関連ツイート分類 (Graph Based Semi-supervised Learning with Convolution Neural Networks to Classify Crisis Related Tweets)</news:title>
   <news:publication_date>2026-04-30T21:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685188</loc>
  <lastmod>2026-04-30T21:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声・映像・テキストの融合による性格予測の最前線（Investigating Audio, Video, and Text Fusion Methods for End-to-End Automatic Personality Prediction）</news:title>
   <news:publication_date>2026-04-30T21:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685186</loc>
  <lastmod>2026-04-30T21:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多パラメータ最適化による磁気光学トラップの制御（Multiparameter optimisation of a magneto-optical trap using deep learning）</news:title>
   <news:publication_date>2026-04-30T21:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685184</loc>
  <lastmod>2026-04-30T21:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス単位の需要予測を用いたフレキシビリティ市場の活用（Utilizing Device-level Demand Forecasting for Flexibility Markets - Full Version）</news:title>
   <news:publication_date>2026-04-30T21:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685182</loc>
  <lastmod>2026-04-30T21:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>占有格子地図における深層畳み込みネットワークによる物体検出と分類 (Object Detection and Classification in Occupancy Grid Maps using Deep Convolutional Networks)</news:title>
   <news:publication_date>2026-04-30T21:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685180</loc>
  <lastmod>2026-04-30T21:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮辞書学習（Compressed Dictionary Learning）</news:title>
   <news:publication_date>2026-04-30T21:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685178</loc>
  <lastmod>2026-04-30T21:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘテロジニアスクラウド上のプライバシー保護型クエリ検索システム（c-SELENE: Privacy-preserving Query Retrieval System on Heterogeneous Cloud Data）</news:title>
   <news:publication_date>2026-04-30T21:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685176</loc>
  <lastmod>2026-04-30T20:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズに強い音声認識を実現する深層敵対的学習（BOOSTING NOISE ROBUSTNESS OF ACOUSTIC MODEL VIA DEEP ADVERSARIAL TRAINING）</news:title>
   <news:publication_date>2026-04-30T20:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685174</loc>
  <lastmod>2026-04-30T20:19:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と映像を用いた覚醒度‑情動軸の深層ネットワーク（A Deep Network for Arousal-Valence Emotion Prediction with Acoustic-Visual Cues）</news:title>
   <news:publication_date>2026-04-30T20:19:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685172</loc>
  <lastmod>2026-04-30T20:18:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡画像に基づく解釈可能な全畳み込み分類（Interpretable Fully Convolutional Classification of Intrapapillary Capillary Loops for Real-Time Detection of Early Squamous Neoplasia）</news:title>
   <news:publication_date>2026-04-30T20:18:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685170</loc>
  <lastmod>2026-04-30T20:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延制約下のレート制御と「範囲予測」アプローチ（Delay-Constrained Rate Control for Real-Time Video Streaming with Bounded Neural Network）</news:title>
   <news:publication_date>2026-04-30T20:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685168</loc>
  <lastmod>2026-04-30T20:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味チャネルとシャノンチャネルの相互適合（Semantic Channel and Shannon’s Channel Mutually Match for Multi-Label Classification）</news:title>
   <news:publication_date>2026-04-30T20:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685166</loc>
  <lastmod>2026-04-30T20:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Perm-Setネット：順序不明・個数不確定な集合を予測する（DEEP PERM-SET NET: LEARN TO PREDICT SETS WITH UNKNOWN PERMUTATION AND CARDINALITY USING DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-04-30T20:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685164</loc>
  <lastmod>2026-04-30T20:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重たい裾をもつデータに強いℓ1回帰（ℓ1-regression with Heavy-tailed Distributions）</news:title>
   <news:publication_date>2026-04-30T20:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685162</loc>
  <lastmod>2026-04-30T19:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な顔認識へのアプローチ（Towards Interpretable Face Recognition）</news:title>
   <news:publication_date>2026-04-30T19:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685160</loc>
  <lastmod>2026-04-30T19:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長短期記憶ネットワークによるテキスト非依存話者認証（Text-Independent Speaker Verification Using Long Short-Term Memory Networks）</news:title>
   <news:publication_date>2026-04-30T19:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685158</loc>
  <lastmod>2026-04-30T19:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配置・配信配列の設計を学習する注意機構ベースの深層ニューラルネットワーク（Placement Delivery Array Design via Attention-Based Deep Neural Network）</news:title>
   <news:publication_date>2026-04-30T19:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685156</loc>
  <lastmod>2026-04-30T19:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化解析辞書学習による画像分類（STRUCTURED ANALYSIS DICTIONARY LEARNING FOR IMAGE CLASSIFICATION）</news:title>
   <news:publication_date>2026-04-30T19:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685154</loc>
  <lastmod>2026-04-30T19:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造感度型マルチスケール深層生成ネットワークによる低線量CTのノイズ低減（Structurally-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising）</news:title>
   <news:publication_date>2026-04-30T19:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685152</loc>
  <lastmod>2026-04-30T19:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データからの遺伝子調節ネットワーク予測（Prediction of a gene regulatory network from gene expression Profiles with Linear Regression and Pearson Correlation Coefficient）</news:title>
   <news:publication_date>2026-04-30T19:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685150</loc>
  <lastmod>2026-04-30T19:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト間で分岐予測精度を動的に改善する方法（Dynamically Improving Branch Prediction Accuracy Between Contexts）</news:title>
   <news:publication_date>2026-04-30T19:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685148</loc>
  <lastmod>2026-04-30T18:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な歩行者検出のための融合深層ニューラルネットワーク（Fused Deep Neural Networks for Efficient Pedestrian Detection）</news:title>
   <news:publication_date>2026-04-30T18:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685146</loc>
  <lastmod>2026-04-30T18:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み-再帰ニューラルネットワークによる音声強調（CONVOLUTIONAL-RECURRENT NEURAL NETWORKS FOR SPEECH ENHANCEMENT）</news:title>
   <news:publication_date>2026-04-30T18:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685144</loc>
  <lastmod>2026-04-30T18:26:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全準同型暗号を用いた安全な顔照合（Secure Face Matching Using Fully Homomorphic Encryption）</news:title>
   <news:publication_date>2026-04-30T18:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685142</loc>
  <lastmod>2026-04-30T18:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>体表から合成X線画像を生成する手法の解説（Generating Synthetic X-ray Images of a Person from the Surface Geometry）</news:title>
   <news:publication_date>2026-04-30T18:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685140</loc>
  <lastmod>2026-04-30T18:25:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドソーシングにおける分類のための決定木設計（Decision Tree Design for Classification in Crowdsourcing Systems）</news:title>
   <news:publication_date>2026-04-30T18:25:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685138</loc>
  <lastmod>2026-04-30T18:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固体調和散乱不変量による分子特性予測（Solid Harmonic Scattering Invariants）</news:title>
   <news:publication_date>2026-04-30T18:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685136</loc>
  <lastmod>2026-04-30T18:24:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォノン駆動によるアナターゼTiO2ナノ粒子の励起子振幅選択的制御（Phonon-Driven Selective Modulation of Exciton Oscillator Strengths in Anatase TiO2 Nanoparticles）</news:title>
   <news:publication_date>2026-04-30T18:24:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685134</loc>
  <lastmod>2026-04-30T17:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり注意学習によるテキスト句のグラウンディング（Weakly Supervised Attention Learning for Textual Phrases Grounding）</news:title>
   <news:publication_date>2026-04-30T17:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685132</loc>
  <lastmod>2026-04-30T17:32:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模変数選択を現実的にする確率的サンプリング手法の進化（Scalable Importance Tempering and Bayesian Variable Selection）</news:title>
   <news:publication_date>2026-04-30T17:32:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685130</loc>
  <lastmod>2026-04-30T17:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Runge-Kuttaの直接離散化で得られる加速（Direct Runge-Kutta Discretization Achieves Acceleration）</news:title>
   <news:publication_date>2026-04-30T17:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685128</loc>
  <lastmod>2026-04-30T17:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ULIRGにおけるAGN駆動流出の定量化（Quantifying the AGN-driven outflows in ULIRGs）</news:title>
   <news:publication_date>2026-04-30T17:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685126</loc>
  <lastmod>2026-04-30T17:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団の準平衡性と亜構造の検証手法の評価（Evaluating Tests of Virialization and Substructure Using Galaxy Clusters in the ORELSE Survey）</news:title>
   <news:publication_date>2026-04-30T17:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685124</loc>
  <lastmod>2026-04-30T17:28:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動核分割へのMask R-CNN適応（Adapting Mask-RCNN for Automatic Nucleus Segmentation）</news:title>
   <news:publication_date>2026-04-30T17:28:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685122</loc>
  <lastmod>2026-04-30T16:37:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LOFARによるMACS J0717.5+3745での電波放射の発見（LOFAR discovery of radio emission in MACS J0717.5+3745）</news:title>
   <news:publication_date>2026-04-30T16:37:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685120</loc>
  <lastmod>2026-04-30T16:36:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SHARDSによるLAEとLBGの同時探査（LAEs and LBGs in the SHARDS Survey）</news:title>
   <news:publication_date>2026-04-30T16:36:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685118</loc>
  <lastmod>2026-04-30T16:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Viscoveryによる意見フォーラムのトレンド追跡（Viscovery: Trend Tracking in Opinion Forums based on Dynamic Topic Models）</news:title>
   <news:publication_date>2026-04-30T16:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685116</loc>
  <lastmod>2026-04-30T16:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識転送で自己教師あり学習を強化する手法（Boosting Self-Supervised Learning via Knowledge Transfer）</news:title>
   <news:publication_date>2026-04-30T16:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685114</loc>
  <lastmod>2026-04-30T16:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衰退したオンラインコミュニティの事後解析（Postmortem Analysis of Decayed Online Social Communities）</news:title>
   <news:publication_date>2026-04-30T16:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685112</loc>
  <lastmod>2026-04-30T16:34:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハミルトニアンモンテカルロの結合と収束（Coupling and Convergence for Hamiltonian Monte Carlo）</news:title>
   <news:publication_date>2026-04-30T16:34:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685110</loc>
  <lastmod>2026-04-30T16:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深く正規化された深度画像による堅牢な顔認識（Robust Face Recognition with Deeply Normalized Depth Images）</news:title>
   <news:publication_date>2026-04-30T16:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685108</loc>
  <lastmod>2026-04-30T15:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTubeにおけるコラボレーションの定量解析（Collaborations on YouTube: From Unsupervised Detection to the Impact on Video and Channel Popularity）</news:title>
   <news:publication_date>2026-04-30T15:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685106</loc>
  <lastmod>2026-04-30T15:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterが明かす抗議行動予測（Twitter Reveals: Using Twitter Analytics to Predict Public Protests）</news:title>
   <news:publication_date>2026-04-30T15:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685104</loc>
  <lastmod>2026-04-30T15:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>液体アルゴンでのARAPUCA装置の試験（Liquid Argon test of the ARAPUCA device）</news:title>
   <news:publication_date>2026-04-30T15:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685102</loc>
  <lastmod>2026-04-30T15:39:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床退院サマリにおけるWord2VecとDoc2Vecを用いた教師なし感情分析（Word2Vec and Doc2Vec in Unsupervised Sentiment Analysis of Clinical Discharge Summaries）</news:title>
   <news:publication_date>2026-04-30T15:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685100</loc>
  <lastmod>2026-04-30T15:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル間対応による教師なしドメイン適応（Sample-to-Sample Correspondence for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-04-30T15:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685098</loc>
  <lastmod>2026-04-30T15:39:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Factorization Machines を用いた知識追跡の応用（Deep Factorization Machines for Knowledge Tracing）</news:title>
   <news:publication_date>2026-04-30T15:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685096</loc>
  <lastmod>2026-04-30T15:39:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル記憶ネットワークの体系化（A Taxonomy for Neural Memory Networks）</news:title>
   <news:publication_date>2026-04-30T15:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
