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Thompson Sampling for the MNL-Bandit.

, , , and . COLT, volume 65 of Proceedings of Machine Learning Research, page 76-78. PMLR, (2017)

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Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory., and . CoRR, (2020)A Doubly Robust Approach to Sparse Reinforcement Learning., , and . CoRR, (2023)Complexity Analysis of a Countable-armed Bandit Problem., and . ALT, volume 201 of Proceedings of Machine Learning Research, page 850-890. PMLR, (2023)Sparsity-Agnostic Lasso Bandit., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 8271-8280. PMLR, (2021)Last Switch Dependent Bandits with Monotone Payoff Functions., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 10265-10284. PMLR, (2023)A Near-Optimal Exploration-Exploitation Approach for Assortment Selection., , , and . EC, page 599-600. ACM, (2016)A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms., and . NeurIPS, page 8807-8819. (2021)Practical Nonparametric Sampling Strategies for Quantile-Based Ordinal Optimization., , and . INFORMS J. Comput., 34 (2): 752-768 (2022)Capacity Sizing Under Parameter Uncertainty: Safety Staffing Principles Revisited., , and . Manag. Sci., 56 (10): 1668-1686 (2010)A Doubly Robust Approach to Sparse Reinforcement Learning., , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 2305-2313. PMLR, (2024)