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@@ -404,10 +404,17 @@ For any question about the paper, data, and pipeline, feel free to contact: ys55
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19. James McInerney, Brian Brost, Praveen Chandar, Rishabh Mehrotra, and Benjamin Carterette. [Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions](https://arxiv.org/abs/2007.12986). In *Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery&Data Mining*, 1779–1788, 2020.
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20.Yusuke Narita, Shota Yasui, and Kohei Yata. [Debiased Off-Policy Evaluation for Recommendation Systems](https://arxiv.org/abs/2002.08536). *arXiv preprint arXiv:2002.08536*, 2020.
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20. Yusuke Narita, Shota Yasui, and Kohei Yata. [Debiased Off-Policy Evaluation for Recommendation Systems](https://dl.acm.org/doi/10.1145/3460231.3474231). In *Proceedings of the Fifteenth ACM Conference on Recommender Systems*, 372-379, 2021.
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21. Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec. [Open Graph Benchmark: Datasets for Machine Learning on Graphs](https://arxiv.org/abs/2005.00687). In *Advances in Neural Information Processing Systems*. 2020.
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22. Noveen Sachdeva, Yi Su, and Thorsten Joachims. [Off-policy Bandits with Deficient Support](https://dl.acm.org/doi/10.1145/3394486.3403139). In *Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining*, 965-975, 2021.
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23. Yi Su, Pavithra Srinath, and Akshay Krishnamurthy. [Adaptive Estimator Selection for Off-Policy Evaluation](https://proceedings.mlr.press/v119/su20d.html). In *Proceedings of the 38th International Conference on Machine Learning*, 9196-9205, 2021.
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24. Haruka Kiyohara, Yuta Saito, Tatsuya Matsuhiro, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto. [Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model](https://dl.acm.org/doi/10.1145/3488560.3498380). In *Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining*, 487-497, 2022.
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25. Yuta Saito and Thorsten Joachims. [Off-Policy Evaluation for Large Action Spaces via Embeddings](https://arxiv.org/abs/2202.06317). In *Proceedings of the 39th International Conference on Machine Learning*, 2022.
@@ -381,10 +381,18 @@ Open Bandit Pipelineへのどんな貢献も歓迎いたします. プロジェ
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19. James McInerney, Brian Brost, Praveen Chandar, Rishabh Mehrotra, and Benjamin Carterette. [Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions](https://arxiv.org/abs/2007.12986). In *Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery&Data Mining*, 1779–1788, 2020.
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20.Yusuke Narita, Shota Yasui, and Kohei Yata. [Debiased Off-Policy Evaluation for Recommendation Systems](https://arxiv.org/abs/2002.08536). *arXiv preprint arXiv:2002.08536*, 2020.
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20. Yusuke Narita, Shota Yasui, and Kohei Yata. [Debiased Off-Policy Evaluation for Recommendation Systems](https://dl.acm.org/doi/10.1145/3460231.3474231). In *Proceedings of the Fifteenth ACM Conference on Recommender Systems*, 372-379, 2021.
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21. Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec. [Open Graph Benchmark: Datasets for Machine Learning on Graphs](https://arxiv.org/abs/2005.00687). In *Advances in Neural Information Processing Systems*. 2020.
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22. Noveen Sachdeva, Yi Su, and Thorsten Joachims. [Off-policy Bandits with Deficient Support](https://dl.acm.org/doi/10.1145/3394486.3403139). In *Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining*, 965-975, 2021.
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23. Yi Su, Pavithra Srinath, and Akshay Krishnamurthy. [Adaptive Estimator Selection for Off-Policy Evaluation](https://proceedings.mlr.press/v119/su20d.html). In *Proceedings of the 38th International Conference on Machine Learning*, 9196-9205, 2021.
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+
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24. Haruka Kiyohara, Yuta Saito, Tatsuya Matsuhiro, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto. [Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model](https://dl.acm.org/doi/10.1145/3488560.3498380). In *Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining*, 487-497, 2022.
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25. Yuta Saito and Thorsten Joachims. [Off-Policy Evaluation for Large Action Spaces via Embeddings](https://arxiv.org/abs/2202.06317). In *Proceedings of the 39th International Conference on Machine Learning*, 2022.
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