linear mixture mdp

Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs ICLR 2024 Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition AISTATS 2024 Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs NeurIPS 2024 Prior-dependent analysis of posterior sampling reinforcement learning with function approximation AISTATS 2024 Dynamic Regret of Adversarial Linear Mixture MDPs NeurIPS 2023 Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs ICML 2023 Optimistic Planning by Regularized Dynamic Programming ICML 2023 Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency COLT 2023 Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs NeurIPS 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 Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs AISTATS 2022 Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP NeurIPS 2021 Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation NeurIPS 2021