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Bandit Algorithms, и . (2019)Thompson Sampling is Asymptotically Optimal in General Environments., , , и . UAI, AUAI Press, (2016)BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback., , , , , , и . UAI, том 115 из Proceedings of Machine Learning Research, стр. 196-206. AUAI Press, (2019)On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits., и . UAI, том 115 из Proceedings of Machine Learning Research, стр. 894-904. AUAI Press, (2019)Model Selection in Contextual Stochastic Bandit Problems., , , , , , и . NeurIPS, (2020)High-Dimensional Sparse Linear Bandits., , и . NeurIPS, (2020)Single-Agent Policy Tree Search With Guarantees., , , и . NeurIPS, стр. 3205-3215. (2018)On the Optimality of Batch Policy Optimization Algorithms., , , , , , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 11362-11371. PMLR, (2021)Leveraging Demonstrations to Improve Online Learning: Quality Matters., , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 12527-12545. PMLR, (2023)Online Learning to Rank with Features., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 3856-3865. PMLR, (2019)