論文

International Conference Proceedings

• Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura, Takanori Muroi, Yusuke Narita, Yuki Sasamoto, Kei Tateno, Takuma Udagawa, Yuta Saito.
  Offline Contextual Bandits in the Presence of New Actions.
  Transactions on Machine Learning Research (TMLR), 2026.

• Ren Kishimoto*, Rikiya Takehi*, Koichi Tanaka, Riku Togashi, Masahiro Nomura, Yoji Tomita, Yuta Saito.
  Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching.
  In Proceedings of the 14th International Conference on Learning Representations (ICLR), 2026.

• Koichi Tanaka*, Ren Kishimoto*, Bushun Kawagishi, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto, Yuta Saito.
  Off-Policy Learning with Limited Supply.
  In Proceedings of the ACM Web Conference (TheWebConf), 2026.

• Ren Kishimoto, Koichi Tanaka, Haruka Kiyohara, Yusuke Narita, Yasuo Yamamoto, Nobuyuki Shimizu, Yuta Saito.
  Efficient Offline Learning of Ranking Policies via Top-k Policy Decomposition.
  ACM Conference on Knowledge and Information Management (CIKM), 2026.

• Tatsuhiro Shimizu*, Koichi Tanaka*, Ren Kishimoto, Haruka Kiyohara, Masahiro Nomura, Yuta Saito.
  Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits.
  In Proceedings of the 18th ACM Recommender Systems Conference (RecSys), 2024.

• Haruka Kiyohara, Ren Kishimoto, Kosuke Kawakami, Ken Kobayashi, Kazuhide Nakata, Yuta Saito.
  Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation.
  In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024.

Domestic Conference

• 岸本 廉, 武樋 力哉, 田中 滉一, 野村 将寛, 冨田 燿志, 齋藤 優太, 冨樫 陸.
  ユーザ継続の最大化を目的とした双方向マッチング.
  2026年度 人工知能学会全国大会（第40回）, 2026.

Workshop

• Kosuke Iguchi, Ren Kishimoto.
  Adaptive Doubly Robust Off-Policy Evaluation for Ranking Policies under Diverse User Behavior.
  RecSys Workshop on Causality, Counterfactuals & Sequential Decision-Making (CONSEQUENCES), 2026.

• Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura, Takanori Muroi, Yusuke Narita, Yuki Sasamoto, Kei Tateno, Takuma Udagawa, Yuta Saito.
  Offline Contextual Bandits in the Presence of New Actions.
  KDD 2025 Workshop - Causal Inference and Machine Learning in Practice.

• Ren Kishimoto*, Koichi Tanaka*, Haruka Kiyohara, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto, Yuta Saito.
  Efficient Offline Learning of Ranking Policies via Top-k Policy Decomposition.
  ICML 2024 Workshop on Aligning Reinforcement Learning Experimentalists and Theorists (ARLET), 2024.

Preprint

• Rikiya Takehi*, Koichi Tanaka*, Ren Kishimoto, Masahiro Nomura, Riku Togashi, Yuta Saito.
  Objective-driven Calibrated Recommendations.
  preprint, 2025.

• Haruka Kiyohara, Ren Kishimoto, Kosuke Kawakami, Ken Kobayashi, Kazuhide Nakata, and Yuta Saito.
  SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation.
  arXiv preprint, 2023.