| Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback Y Saito, S Yaginuma, Y Nishino, H Sakata, K Nakata Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 363 | 2020 |
| Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback Y Saito Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 136 | 2020 |
| Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation Y Saito, A Shunsuke, M Matsutani, N Yusuke https://arxiv.org/abs/2008.07146, 2020 | 135* | 2020 |
| Doubly robust estimator for ranking metrics with post-click conversions Y Saito Proceedings of the 14th ACM Conference on Recommender Systems, 92-100, 2020 | 97 | 2020 |
| Counterfactual learning and evaluation for recommender systems: Foundations, implementations, and recent advances Y Saito, T Joachims Proceedings of the 15th ACM Conference on Recommender Systems, 828-830, 2021 | 80 | 2021 |
| Unbiased pairwise learning from biased implicit feedback Y Saito Proceedings of the 2020 ACM SIGIR on International Conference on Theory of …, 2020 | 78* | 2020 |
| Off-policy evaluation for large action spaces via embeddings Y Saito, T Joachims arXiv preprint arXiv:2202.06317, 2022 | 73 | 2022 |
| 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 | 60 | 2022 |
| Counterfactual cross-validation: Stable model selection procedure for causal inference models Y Saito, S Yasui International Conference on Machine Learning, 8398-8407, 2020 | 52* | 2020 |
| 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 | 51 | 2021 |
| Optimal off-policy evaluation from multiple logging policies N Kallus, Y Saito, M Uehara International Conference on Machine Learning, 5247-5256, 2021 | 46 | 2021 |
| Off-policy evaluation for large action spaces via conjunct effect modeling Y Saito, Q Ren, T Joachims international conference on Machine learning, 29734-29759, 2023 | 42 | 2023 |
| Fair ranking as fair division: Impact-based individual fairness in ranking Y Saito, T Joachims Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 36 | 2022 |
| Doubly robust prediction and evaluation methods improve uplift modeling for observational data Y Saito, H Sakata, K Nakata Proceedings of the 2019 SIAM International Conference on Data Mining, 468-476, 2019 | 30 | 2019 |
| 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 | 26 | 2023 |
| Dual Learning Algorithm for Delayed Feedback in Display Advertising Y Saito, G Morishita, S Yasui Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 23* | 2020 |
| 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 | 19 | 2023 |
| Off-policy evaluation of slate bandit policies via optimizing abstraction H Kiyohara, M Nomura, Y Saito Proceedings of the ACM Web Conference 2024, 3150-3161, 2024 | 18 | 2024 |
| Towards resolving propensity contradiction in offline recommender learning Y Saito, M Nomura arXiv preprint arXiv:1910.07295, 2019 | 18 | 2019 |
| Towards assessing and benchmarking risk-return tradeoff of off-policy evaluation H Kiyohara, R Kishimoto, K Kawakami, K Kobayashi, K Nakata, Y Saito arXiv preprint arXiv:2311.18207, 2023 | 17 | 2023 |
