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Offline RL

725 directly classified papers

Papers per year

Papers

Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding NIPS 2020
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation NIPS 2020
MOReL: Model-Based Offline Reinforcement Learning NIPS 2020
BRPO: Batch Residual Policy Optimization IJCAI 2020
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes JMLR 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning CORL 2020
PLAS: Latent Action Space for Offline Reinforcement Learning CORL 2020
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning AISTATS 2020
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning AISTATS 2020
A Nonparametric Off-Policy Policy Gradient AISTATS 2020
Conditional Importance Sampling for Off-Policy Learning AISTATS 2020
Adaptive Trade-Offs in Off-Policy Learning AISTATS 2020
Scaling data-driven robotics with reward sketching and batch reinforcement learning RSS 2020
Human-centric dialog training via offline reinforcement learning EMNLP 2020
Off-Policy Evaluation in Partially Observable Environments AAAI 2020
Attentive Experience Replay AAAI 2020
BAR — A Reinforcement Learning Agent for Bounding-Box Automated Refinement AAAI 2020
Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation ICML 2020
GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values ICML 2020
Adaptive Estimator Selection for Off-Policy Evaluation ICML 2020
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits ICML 2020
Off-Policy Actor-Critic with Shared Experience Replay ICML 2020
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning ICML 2020
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling ICML 2020
Batch Reinforcement Learning with Hyperparameter Gradients ICML 2020