| Doubly robust off-policy evaluation for ranking policies under the cascade behavior model H Kiyohara, Y Saito, T Matsuhiro, Y Narita, N Shimizu, Y Yamamoto Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 38 | 2022 |
| Evaluating the robustness of off-policy evaluation Y Saito, T Udagawa, H Kiyohara, K Mogi, Y Narita, K Tateno Proceedings of the 15th ACM Conference on Recommender Systems, 114-123, 2021 | 28 | 2021 |
| Future-dependent value-based off-policy evaluation in pomdps M Uehara, H Kiyohara, A Bennett, V Chernozhukov, N Jiang, N Kallus, ... Advances in Neural Information Processing Systems 36, 2024 | 12 | 2024 |
| Policy-adaptive estimator selection for off-policy evaluation T Udagawa, H Kiyohara, Y Narita, Y Saito, K Tateno Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 10025 …, 2023 | 11 | 2023 |
| Accelerating offline reinforcement learning application in real-time bidding and recommendation: Potential use of simulation H Kiyohara, K Kawakami, Y Saito arXiv preprint arXiv:2109.08331, 2021 | 8 | 2021 |
| Off-policy evaluation of ranking policies under diverse user behavior H Kiyohara, M Uehara, Y Narita, N Shimizu, Y Yamamoto, Y Saito Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 3 | 2023 |
| SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation H Kiyohara, R Kishimoto, K Kawakami, K Kobayashi, K Nakata, Y Saito arXiv preprint arXiv:2311.18206, 2023 | 2 | 2023 |
| Towards assessing and benchmarking risk-return tradeoff of off-policy evaluation H Kiyohara, R Kishimoto, K Kawakami, K Kobayashi, K Nakata, Y Saito The Twelfth International Conference on Learning Representations, 2023 | 2 | 2023 |
| Constrained Generalized Additive 2 Model With Consideration of High-Order Interactions A Watanabe, M Kuramata, K Majima, H Kiyohara, K Kensho, K Nakata 2021 International Conference on Electrical, Computer and Energy …, 2021 | 2 | 2021 |
| Off-policy evaluation of slate bandit policies via optimizing abstraction H Kiyohara, M Nomura, Y Saito arXiv preprint arXiv:2402.02171, 2024 | 1 | 2024 |
Yuta SaitoCornell UniversityVerified email at cornell.edu
