113 citations · 1k across the 66 of their papers we have counts for
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An Empirical Study of Implicit Regularization in Deep Offline RL
Caglar Gulcehre, Srivatsan Srinivasan, Jakub Sygnowski +5
Deep neural networks are the most commonly used function approximators in offline reinforcement learning. Prior works have shown that neural nets trained with TD-learning and gradi…
Continual Learning Beyond a Single Model
Thang Doan, Seyed Iman Mirzadeh, Mehrdad Farajtabar
A growing body of research in continual learning focuses on the catastrophic forgetting problem. While many attempts have been made to alleviate this problem, the majority of the m…
Architecture Matters in Continual Learning
Seyed Iman Mirzadeh, Arslan Chaudhry, Dong Yin +4
A large body of research in continual learning is devoted to overcoming the catastrophic forgetting of neural networks by designing new algorithms that are robust to the distributi…