nonlinear function approximation

Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications AISTATS 2024 Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning COLT 2024 PILOT: An O(1/K)-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation ICLR 2024 VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation COLT 2023 Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022 On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL NeurIPS 2022 Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature NeurIPS 2021 Provably Correct Optimization and Exploration with Non-linear Policies ICML 2021 Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms AISTATS 2021 Geometric Insights into the Convergence of Nonlinear TD Learning ICLR 2020 Gradient Temporal-Difference Learning with Regularized Corrections ICML 2020 Online Multi-Kernel Learning with Graph-Structured Feedback ICML 2020 Zap Q-Learning With Nonlinear Function Approximation NeurIPS 2020 Convergent Policy Optimization for Safe Reinforcement Learning NeurIPS 2019 Two-Timescale Networks for Nonlinear Value Function Approximation ICLR 2019 Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning NeurIPS 2019 Exponentially Weighted Imitation Learning for Batched Historical Data NeurIPS 2018 SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation ICML 2018