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Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL.

, , , , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 2488-2497. PMLR, (2023)

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Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes., , and . CoRR, (2020)Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium., , , and . NeurIPS, (2022)Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency., , , , and . COLT, volume 195 of Proceedings of Machine Learning Research, page 4977-5020. PMLR, (2023)Uncertainty-Aware Reward-Free Exploration with General Function Approximation., , , and . CoRR, (2024)Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks., , , and . CoRR, (2018)Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL., , , , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 2488-2497. PMLR, (2023)Logarithmic Regret for Reinforcement Learning with Linear Function Approximation., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 4171-4180. PMLR, (2021)Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 4430-4440. PMLR, (2020)Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization., , and . NeurIPS, page 3925-3936. (2018)Lower Bounds for Smooth Nonconvex Finite-Sum Optimization., and . ICML, volume 97 of Proceedings of Machine Learning Research, page 7574-7583. PMLR, (2019)