18 citations · 67 across the 12 of their papers we have counts for
4 papers · 1 filter
Vision-Language Models as a Source of Rewards
Kate Baumli, Satinder Baveja, Feryal Behbahani +24
Building generalist agents that can accomplish many goals in rich open-ended environments is one of the research frontiers for reinforcement learning. A key limiting factor for bui…
In-context Reinforcement Learning with Algorithm Distillation
Michael Laskin, Luyu Wang, Junhyuk Oh +11
We propose Algorithm Distillation (AD), a method for distilling reinforcement learning (RL) algorithms into neural networks by modeling their training histories with a causal seque…
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise
Yeming Wen, Kevin Luk, Maxime Gazeau +3
The choice of batch-size in a stochastic optimization algorithm plays a substantial role for both optimization and generalization. Increasing the batch-size used typically improves…
A general system of differential equations to model first order adaptive algorithms
André Belotto da Silva, Maxime Gazeau
First order optimization algorithms play a major role in large scale machine learning. A new class of methods, called adaptive algorithms, were recently introduced to adjust iterat…