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12/29/2022
Offline Policy Optimization in RL with Variance Regularizaton
Learning policies from fixed offline datasets is a key challenge to scal...
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12/28/2022
Representation Learning in Deep RL via Discrete Information Bottleneck
Several self-supervised representation learning methods have been propos...
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12/31/2021
Single-Shot Pruning for Offline Reinforcement Learning
Deep Reinforcement Learning (RL) is a powerful framework for solving com...
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12/31/2021
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning
We hypothesize that empirically studying the sample complexity of offlin...
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05/03/2020
Off-Policy Adversarial Inverse Reinforcement Learning
Adversarial Imitation Learning (AIL) is a class of algorithms in Reinfor...
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12/11/2019