国際会議発表 (査読有り)

• Yuta Saito, Hayato Sakata, Kazuhide Nakata. Cost-Effective and Stable Policy Optimization Algorithm for Uplift Modeling with Multiple Treatments, SIAM International Conference on Data Mining (SDM20), Proceedings of SIAM International Conference on Data Mining (SDM20), pp. 406-414, May 2020.
• Yuta Saito, Suguru Yaginuma, Yuta Nishino, Hayato Sakata, Kazuhide Nakata. Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback, The 13th ACM International WSDM Conference (WSDM2020), Proceedings of The 13th ACM International WSDM Conference, pp. 501-509, Feb. 2020.
• Yuta Saito, Hayato Sakata, Kazuhide Nakata. Doubly Robust Prediction and Evaluation Methods Improve Uplift Modeling for Observational Data, SIAM International Conference on Data Mining (SDM19), Proceedings of SIAM International Conference on Data Mining (SDM19), Vol. 70, pp. 431-446, May 2019.

その他の論文・著書など

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

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