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Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice., , , , , , , , , and 5 other author(s). ICML, volume 202 of Proceedings of Machine Learning Research, page 17135-17175. PMLR, (2023)Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning., , and . CoRR, (2021)Internet and mobile phone text-messaging dependency: Factor structure and correlation with dysphoric mood among Japanese adults., , , , , and . Comput. Hum. Behav., 27 (5): 1702-1709 (2011)KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal., , , , , , , , , and 3 other author(s). CoRR, (2022)ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives., and . CoRR, (2021)A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees., , , , , , , , and . CoRR, (2024)Cautious Actor-Critic., , and . ACML, volume 157 of Proceedings of Machine Learning Research, page 220-235. PMLR, (2021)Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning., , and . ACML, volume 157 of Proceedings of Machine Learning Research, page 918-931. PMLR, (2021)