Offline Reinforcement Learning

Preference Elicitation for Offline Reinforcement Learning ICLR 2025 Robust Offline Policy Learning with Observational Data from Multiple Sources AISTATS 2025 SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation ICLR 2025 Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning ICLR 2024 Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL NeurIPS 2024 DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors NeurIPS 2024 Doubly Mild Generalization for Offline Reinforcement Learning NeurIPS 2024 Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning (Abstract Reprint) AAAI 2024 Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization NeurIPS 2024 Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning NeurIPS 2024 MetaReflection: Learning Instructions for Language Agents using Past Reflections EMNLP 2024 Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NeurIPS 2024 Multi-Agent Domain Calibration with a Handful of Offline Data NeurIPS 2024 Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPs UAI 2024 Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data COLT 2024 Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression NeurIPS 2024 Offline RL with Observation Histories: Analyzing and Improving Sample Complexity ICLR 2024 Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning ICLR 2024 PISDR: Page and Item Sequential Decision for Re-ranking Based on Offline Reinforcement Learning ACML 2024 Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers NeurIPS 2024 RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation NeurIPS 2024 Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach AAAI 2024 Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning NeurIPS 2024 Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction AAAI 2024 The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning NeurIPS 2024