13 citations · 21 across the 12 of their papers we have counts for
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cs.LG2023
On Double Descent in Reinforcement Learning with LSTD and Random Features
David Brellmann, Eloïse Berthier, David Filliat +1
Temporal Difference (TD) algorithms are widely used in Deep Reinforcement Learning (RL). Their performance is heavily influenced by the size of the neural network. While in supervi…
cs.LG2023
VIBR: Learning View-Invariant Value Functions for Robust Visual Control
Tom Dupuis, Jaonary Rabarisoa, Quoc-Cuong Pham +1
End-to-end reinforcement learning on images showed significant progress in the recent years. Data-based approach leverage data augmentation and domain randomization while represent…