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07/25/2023
Offline Reinforcement Learning with On-Policy Q-Function Regularization
The core challenge of offline reinforcement learning (RL) is dealing wit...
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07/15/2023
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation
Robustness has been extensively studied in reinforcement learning (RL) t...
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05/26/2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
This paper investigates model robustness in reinforcement learning (RL) ...
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10/18/2022
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation
Curriculum Reinforcement Learning (CRL) aims to create a sequence of tas...
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08/11/2022
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity
This paper concerns the central issues of model robustness and sample ef...
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04/11/2022
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
This paper is concerned with offline reinforcement learning (RL), which ...
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02/28/2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
Offline or batch reinforcement learning seeks to learn a near-optimal po...
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10/09/2021
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
Achieving sample efficiency in online episodic reinforcement learning (R...
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11/25/2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently
Multi-channel sparse blind deconvolution, or convolutional sparse coding...
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12/01/2017