off-policy learning

Adaptive Exploration for Data-Efficient General Value Function Evaluations NeurIPS 2024 Adversarial Imitation Learning via Boosting ICLR 2024 AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents ICLR 2024 Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion EMNLP 2024 Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment ICLR 2024 Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate NeurIPS 2024 Enhancing Off-Policy Constrained Reinforcement Learning through Adaptive Ensemble C Estimation AAAI 2024 Fair Off-Policy Learning from Observational Data ICML 2024 Genetic-guided GFlowNets for Sample Efficient Molecular Optimization NeurIPS 2024 Hyperparameter Optimization Can Even Be Harmful in Off-Policy Learning and How to Deal with It IJCAI 2024 Improving Autonomous Separation Assurance through Distributed Reinforcement Learning with Attention Networks AAAI 2024 Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees ICLR 2024 Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning JMLR 2024 Off-Policy Primal-Dual Safe Reinforcement Learning ICLR 2024 Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning ICLR 2024 Skill or Luck? Return Decomposition via Advantage Functions ICLR 2024 The Curse of Diversity in Ensemble-Based Exploration ICLR 2024 Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling UAI 2024 WPO: Enhancing RLHF with Weighted Preference Optimization EMNLP 2024 A CMDP-within-online framework for Meta-Safe Reinforcement Learning ICLR 2023 Adaptive Estimation Q-learning with Uncertainty and Familiarity IJCAI 2023 A policy gradient approach for optimization of smooth risk measures UAI 2023 A Pragmatic Look at Deep Imitation Learning ACML 2023 Backstepping Temporal Difference Learning ICLR 2023 Boosted Off-Policy Learning AISTATS 2023