加藤真大

論文

研究業績の一覧です．引用情報は Google Scholar もご覧ください．

ワーキングペーパー

  • Masahiro Kato, Kyohei Okumura, Takuya Ishihara, and Toru Kitagawa. "Adaptive Experimental Design for Policy Learning" arXiv
  • Masahiro Kato, Kei Nakagawa, Kenshi Abe, Tetsuro Morimura, and Kentaro Baba. "Direct Expected Quadratic Utility Maximization for Mean-Variance Controlled Reinforcement Learning" arXiv
  • Masahiro Kato, Kota Matsui, and Ryo Inokuchi. "Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation"（投稿中） arXiv
  • Masahiro Kato. "Adaptive Generalized Neyman Allocation: Local Asymptotic Minimax Optimal Best Arm Identification"（投稿中） arXiv
  • Kaito Ariu, Masahiro Kato, Junpei Komiyama, Kenichiro McAlinn, and Chao Qin. "A Comment on "Adaptive Treatment Assignment in Experiments for Policy Choice"" 2021. Revise and Resubmit for Econometrica.
  • Masahiro Kato, Takuya Ishihara, Junya Honda, and Yusuke Narita. "Efficient Adaptive Experimental Design for Average Treatment Effect Estimation" Revise and Resubmit for JASA. arXiv

国際会議紀要

  • Masahiro Kato. "General Bayesian Policy Learning" In the Conference on Uncertainty in Artificial Intelligence (UAI), 2026.
  • Masahiro Kato. "ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation" In the International Conference on Machine Learning (ICML), 2026.
  • Kiet Q. H. Vo, Siu Lun Chau, Masahiro Kato, Yixin Wang, and Krikamol Muandet. "Strategic Learning with Local Explanations as Feedback" In the International Conference on Artificial Intelligence and Statistics (AISTATS), 2026. arXiv
  • Masahiro Kato, Fumiaki Kozai, and Ryo Inokuchi. "PUATE: Semiparametric Efficient Average Treatment Effect Estimation from Treated (Positive) and Unlabeled Units" In the Advances in Neural Information Processing Systems (NeurIPS), 2025.
  • Yuika Shiina*, Masahiro Kato, and Ryo Inokuchi. "Analysis of the Keiki Watchers Survey using Independent Component Analysis and Linear Discriminant Analysis" In the 3rd International Conference on Computational and Data Sciences in Economics and Finance (CDEF), 2025.
  • Masahiro Kato*, Yuki Ikeda, Kentaro Baba, Takashi Imai, and Ryo Inokuchi. "Learning from Double Positive and Unlabeled Data for Potential-Customer Identification" In the 3rd International Conference on Computational and Data Sciences in Economics and Finance (CDEF), 2025.
  • Masahiro Kato*. "Neyman Allocation for Two-Armed Gaussian Best-Arm Identification with Unknown Variances" In the 3rd International Conference on Computational and Data Sciences in Economics and Finance (CDEF), 2025.
  • Masahiro Kato* and Shinji Ito. "LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits" In the International Conference on Artificial Intelligence and Statistics (AISTATS), 2025. openreview
  • Masahiro Kato*. "Analysis of the Temporal Structure in Economic Condition Assessments" In IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), 2024. IEEE
  • Masahiro Kato*, Kentaro Baba, Hibiki Kaibuchi, and Ryo Inokuchi. "Bayesian Portfolio Optimization by Predictive Synthesis" In IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), 2024. IEEE
  • Masahiro Kato*, Akihiro Oga, Wataru Komatsubara, and Ryo Inokuchi. "Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices" In the International Conference on Machine Learning (ICML, Oral 1.5%), 2024. PMLR スライド
  • Masahiro Kato*, Masaaki Imaizumi, and Kentaro Minami. "Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics" In the International Conference on Artificial Intelligence and Statistics (AISTATS), 2023. arXiv
  • Shota Yasui* and Masahiro Kato* (*Equal contribution). "Learning Classifiers under Delayed Feedback with a Time Window Assumption" In the International Conference on Knowledge Discovery and Data Mining (KDD), 2022. ACM
  • Masahiro Kato*, Masaaki Imaizumi, Kenichiro McAlinn, Shota Yasui, and Haruo Kakehi. "Learning Causal Models from Conditional Moment Restrictions by Importance Weighting" In the International Conference on Learning Representations (ICLR, Spotlight 4% 176/3391), 2022. openreview
  • Masahiro Kato*, Kenichiro McAlinn, and Shota Yasui. "The Adaptive Doubly Robust Estimator and a Paradox Concerning Logging Policy" In the Advances in Neural Information Processing Systems (NeurIPS), 2021. openreview
  • Masahiro Kato* and Takeshi Teshima. "Non-negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation" In the International Conference on Machine Learning (ICML), 2021. PMLR
  • Riku Togashi, Masahiro Kato, Mayu Otani, Tetsuya Sakai, and Shin'ichi Satoh. "Scalable Personalised Item Ranking through Parametric Density Estimation" In the Conference on Research and Development in Information Retrieval (SIGIR), 2021. ACM
  • Riku Togashi, Masahiro Kato, Mayu Otani, and Shin'ichi Satoh. "Density-Ratio Based Personalised Ranking from Implicit Feedback" In the Web Conference (WWW), 2021. ACM
  • Masatoshi Uehara*, Masahiro Kato*, and Shota Yasui (*Equal contribution). "Off-Policy Evaluation and Learning for External Validity under a Covariate Shift" In the Advances in Neural Information Processing Systems (NeurIPS, Spotlight 3% 280/9054), 2020. NeurIPS
  • Masahiro Kato*, Takeshi Teshima, and Junya Honda. "Learning from Positive and Unlabeled Data with a Selection Bias" In the International Conference on Learning Representations (ICLR), 2019. openreview

* は主著者または共同主著者を表します．

国際学術誌

  • Masahiro Kato and Akari Ohda. "Asymptotically Unbiased Synthetic Control Methods by Density Matching" Journal of Causal Inference. arXiv
  • Masahiro Kato and Kaito Ariu. "The Role of Contextual Information in Best Arm Identification" Journal of Machine Learning Research (JMLR).
  • Junpei Komiyama, Kaito Ariu, Masahiro Kato, and Chao Qin. "Optimal Simple Regret in Bayesian Best Arm Identification" Mathematics of Operations Research.
  • Masahiro Kato and Shinji Ito. "Best-of-Both-Worlds Linear Contextual Bandits" Transactions on Machine Learning Research (TMLR).

国内会議紀要

  • Masahiro Kato. "Conformal Predictive Portfolio Selection" JAFEE 2024 冬季大会． arXiv
  • 椎名唯圭，加藤真大，井口亮．「独立成分分析とFisherの線形判別による内閣府景気ウォッチャー調査データの分析」言語処理学会 第31回年次大会． 論文
  • 加藤真大，浦川通，田口雄哉，新妻巧朗，田森秀明，羽根田賢和，持橋大地．「線形判別分析のPU学習による朝日歌壇短歌の分析」言語処理学会 第31回年次大会． 論文
  • 加藤真大，浦川通，田口雄哉，新妻巧朗，田森秀明，羽根田賢和，持橋大地．「文埋め込みに基づく朝日歌壇短歌の分析」
  • 井口亮，加藤真大，貝淵響，野田俊也，今泉允聡．「密度比マッチングと勾配コミュニケーションによる異質性を伴う連合学習」第32回 人工知能学会 金融情報学研究会（SIG-FIN）． 論文
  • 馬場健太郎，加藤真大，今井岳．「二重PU学習による潜在的顧客の特定」第32回 人工知能学会 金融情報学研究会（SIG-FIN）． 論文
  • 加藤真大，貝淵響．「ベイジアン予測統合に基づくポートフォリオ選択」第32回 人工知能学会 金融情報学研究会（SIG-FIN）． 論文

ワークショップでの発表

  • Akira Fukuda, Masahiro Kato, Kenichiro McAlinn, and Kosaku Takanashi. "Bayesian Predictive Synthetic Control Methods" In ICML 2023 Workshop on Counterfactuals in Minds and Machines. 資料
  • Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara, and Toru Kitagawa. "Fixed-Budget Hypothesis Best Arm Identification: On the Information Loss in Experimental Design" In ICML 2023 Workshop on New Frontiers in Learning, Control, and Dynamical Systems. openreview
  • Masahiro Kato. "Best Arm Identification with a Fixed Budget under a Small Gap" Allied Social Sciences Association (ASSA) 2023 Annual Meeting. スライド
  • Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara, and Toru Kitagawa. "Semiparametric Best Arm Identification with Contextual Information" In IBIS 2022. arXiv ポスター
  • 加藤真大．「経済学と機械学習：因果推論と密度比推定を中心に」統計・機械学習若手シンポジウム 2022． スライド
  • Masahiro Kato. "Recent Findings on Density-Ratio Approaches in Machine Learning" Workshop on Functional Inference and Machine Intelligence (FIMI), 2022.
  • Masahiro Kato, Masaaki Imaizumi, Kenichiro McAlinn, Shota Yasui, and Haruo Kakehi. "Learning Causal Relationships from Conditional Moment Conditions by Importance Weighting" In NeurIPS 2021 Workshop on Machine Learning meets Econometrics. arXiv
  • Masahiro Kato, Kei Nakagawa, Kenshi Abe, and Tetsuro Morimura. "Direct Expected Quadratic Utility Maximization for Mean-Variance Controlled Reinforcement Learning" In NeurIPS 2021 Workshop on Deep Reinforcement Learning. arXiv
  • 加藤真大．「効率的な因果推論と意思決定のための実験計画において異質性が果たす役割」統計関連学会連合大会 2021． スライド
  • Masahiro Kato, Shota Yasui, and Kenichiro McAlinn. "The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments" In ICML 2021 Workshop on The Neglected Assumptions In Causal Inference. arXiv
  • Masahiro Kato, Takuya Ishihara, Junya Honda, and Yusuke Narita. "Adaptive Experimental Design for Efficient Treatment Effect Estimation" In NeurIPS 2020 Workshop on Causal Discovery & Causality-Inspired Machine Learning.
  • 加藤真大．「平均処置効果の推定のための適応的実験計画」慶應計量経済学ワークショップ 2020． スライド

その他

  • Masahiro Kato, Kei Nakagawa, Kenshi Abe, Tetsuro Morimura, and Kentaro Baba. "Direct Expected Quadratic Utility Maximization for Mean-Variance Controlled Reinforcement Learning" In the IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)．採択（紀要には掲載せず）． arXiv
  • Masahiro Kato. "A Note on Doubly Robust Estimator in Regression Discontinuity Designs" テクニカルノート． arXiv