linear function approximation

Ordering-based Conditions for Global Convergence of Policy Gradient Methods NeurIPS 2023 Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation NeurIPS 2023 Provably Efficient Model-Free Algorithms for Non-stationary CMDPs AISTATS 2023 Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation L4DC 2023 Refined Regret for Adversarial MDPs with Linear Function Approximation ICML 2023 Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space ICML 2023 Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds NeurIPS 2023 Adaptive Multi-Goal Exploration AISTATS 2022 Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation AISTATS 2022 Computational-Statistical Gap in Reinforcement Learning COLT 2022 Confident Least Square Value Iteration with Local Access to a Simulator AISTATS 2022 Efficient local planning with linear function approximation ALT 2022 First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach ICML 2022 Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation ICML 2022 Learning Stochastic Shortest Path with Linear Function Approximation ICML 2022 Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes ACML 2022 Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation AISTATS 2022 Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation ICML 2022 On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation NeurIPS 2022 On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs ICML 2022 Provably Efficient Model-Free Constrained RL with Linear Function Approximation NeurIPS 2022 Proximal Point Imitation Learning NeurIPS 2022 Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation ICML 2022 Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency ICML 2022 Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation AISTATS 2022