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Offline RL

725 directly classified papers

Papers per year

Papers

Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality NIPS 2024
Neural Network Approximation for Pessimistic Offline Reinforcement Learning AAAI 2024
ODRL: A Benchmark for Off-Dynamics Reinforcement Learning NIPS 2024
Probabilistic Offline Policy Ranking with Approximate Bayesian Computation AAAI 2024
Federated Ensemble-Directed Offline Reinforcement Learning NIPS 2024
Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations AAAI 2024
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support NIPS 2024
Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction AAAI 2024
Enhancing Off-Policy Constrained Reinforcement Learning through Adaptive Ensemble C Estimation AAAI 2024
Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement NIPS 2024
The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning NIPS 2024
Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NIPS 2024
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning NIPS 2024
Minimax-optimal reward-agnostic exploration in reinforcement learning COLT 2024
Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity NIPS 2024
Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL AAAI 2024
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning JMLR 2024
Data-Efficient Policy Evaluation Through Behavior Policy Search JMLR 2024
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards AISTATS 2024
Learning Versatile Skills with Curriculum Masking NIPS 2024
Oracle-Efficient Pessimism: Offline Policy Optimization In Contextual Bandits AISTATS 2024
Offline Policy Learning via Skill-step Abstraction for Long-horizon Goal-Conditioned Tasks IJCAI 2024
Offline Policy Evaluation and Optimization Under Confounding AISTATS 2024
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation NIPS 2024
WPO: Enhancing RLHF with Weighted Preference Optimization EMNLP 2024