495 citations · 721 across the 24 of their papers we have counts for
4 papers · 1 filter
Generalization Through the Lens of Learning Dynamics
Clare Lyle
A machine learning (ML) system must learn not only to match the output of a target function on a training set, but also to generalize to novel situations in order to yield accurate…
Understanding Self-Predictive Learning for Reinforcement Learning
Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond +13
We study the learning dynamics of self-predictive learning for reinforcement learning, a family of algorithms that learn representations by minimizing the prediction error of their…
Learning Dynamics and Generalization in Reinforcement Learning
Clare Lyle, Mark Rowland, Will Dabney +2
Solving a reinforcement learning (RL) problem poses two competing challenges: fitting a potentially discontinuous value function, and generalizing well to new observations. In this…
Understanding and Preventing Capacity Loss in Reinforcement Learning
Clare Lyle, Mark Rowland, Will Dabney
The reinforcement learning (RL) problem is rife with sources of non-stationarity, making it a notoriously difficult problem domain for the application of neural networks. We identi…