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Sample Complexity and Overparameterization Bounds for Temporal-Difference Learning With Neural Network Approximation., , , and . IEEE Trans. Autom. Control., 68 (5): 2891-2905 (May 2023)Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization., , , and . CoRR, (2023)Optimization for Reinforcement Learning: From Single Agent to Cooperative Agents., , , and . CoRR, (2019)Kernel Conditional Moment Constraints for Confounding Robust Inference., and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 650-674. PMLR, (2023)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)Parameter-Agnostic Optimization under Relaxed Smoothness., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 4861-4869. PMLR, (2024)Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence., and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3493-3501. PMLR, (2024)Provably Convergent Policy Optimization via Metric-aware Trust Region Methods., , , and . Trans. Mach. Learn. Res., (2023)Stochastic Primal-Dual Q-Learning Algorithm For Discounted MDPs., and . ACC, page 4897-4902. IEEE, (2019)Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 4281-4308. PMLR, (2022)