Reinforcement Learning

Prediction and Control in Continual Reinforcement Learning NeurIPS 2023 Preference learning for guiding the tree search in continuous POMDPs CoRL 2023 Preserving Privacy Through Dememorization: An Unlearning Technique For Mitigating Memorization Risks In Language Models EMNLP 2023 Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning NeurIPS 2023 Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials RSS 2023 Principled Offline RL in the Presence of Rich Exogenous Information ICML 2023 Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons ICML 2023 Prioritizing Samples in Reinforcement Learning with Reducible Loss NeurIPS 2023 Probabilistic Inference in Reinforcement Learning Done Right NeurIPS 2023 Probabilistic Robustness for Data Filtering EACL 2023 Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits ICML 2023 Provable Benefits of Representational Transfer in Reinforcement Learning COLT 2023 Provable Hierarchy-Based Meta-Reinforcement Learning AISTATS 2023 Provable Reset-free Reinforcement Learning by No-Regret Reduction ICML 2023 Provable Safe Reinforcement Learning with Binary Feedback AISTATS 2023 Provable Sim-to-real Transfer in Continuous Domain with Partial Observations ICLR 2023 Provably Efficient Adversarial Imitation Learning with Unknown Transitions UAI 2023 Provably Efficient Algorithm for Nonstationary Low-Rank MDPs NeurIPS 2023 Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning L4DC 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 Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability NeurIPS 2023 Provably Efficient Offline Reinforcement Learning in Regular Decision Processes NeurIPS 2023 Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources ICML 2023 Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints AAAI 2023