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Leveraging Good Representations in Linear Contextual Bandits.

, , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 8371-8380. PMLR, (2021)

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Improved Algorithms for Conservative Exploration in Bandits., , , and . AAAI, page 3962-3969. AAAI Press, (2020)A Provably Efficient Sample Collection Strategy for Reinforcement Learning., , , and . NeurIPS, page 7611-7624. (2021)Transfer from Multiple MDPs., and . NIPS, page 1746-1754. (2011)Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs., , , and . NeurIPS, page 4891-4900. (2019)Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees., , , , and . NeurIPS, (2022)Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning., , , and . ICLR, OpenReview.net, (2022)Near-linear time Gaussian process optimization with adaptive batching and resparsification., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 1295-1305. PMLR, (2020)Top K Ranking for Multi-Armed Bandit with Noisy Evaluations., , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 6242-6269. PMLR, (2022)A general sample complexity analysis of vanilla policy gradient., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 3332-3380. PMLR, (2022)Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model., , , and . ALT, volume 132 of Proceedings of Machine Learning Research, page 1157-1178. PMLR, (2021)