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Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 1753-1800. PMLR, (2023)Kernel Conditional Moment Constraints for Confounding Robust Inference., and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 650-674. PMLR, (2023)Optimization for Reinforcement Learning: From Single Agent to Cooperative Agents., , , and . CoRR, (2019)Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization., , , and . CoRR, (2023)Sample Complexity and Overparameterization Bounds for Temporal-Difference Learning With Neural Network Approximation., , , and . IEEE Trans. Autom. Control., 68 (5): 2891-2905 (May 2023)Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence., and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3493-3501. PMLR, (2024)Parameter-Agnostic Optimization under Relaxed Smoothness., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 4861-4869. PMLR, (2024)Periodic Q-Learning., and . L4DC, volume 120 of Proceedings of Machine Learning Research, page 582-598. PMLR, (2020)Efficiently Escaping Saddle Points for Non-Convex Policy Optimization., , , , and . CoRR, (2023)Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 9827-9869. PMLR, (2023)