11 citations · 14 across the 4 of their papers we have counts for
4 papers
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…
Confident Approximate Policy Iteration for Efficient Local Planning in -realizable MDPs
Gellért Weisz, András György, Tadashi Kozuno +1
We consider approximate dynamic programming in -discounted Markov decision processes and apply it to approximate planning with linear value-function approximation. Our first con…
On the Role of Neural Collapse in Transfer Learning
Tomer Galanti, András György, Marcus Hutter
We study the ability of foundation models to learn representations for classification that are transferable to new, unseen classes. Recent results in the literature show that repre…
Non-Stationary Delayed Bandits with Intermediate Observations
Claire Vernade, Andras Gyorgy, Timothy Mann
Online recommender systems often face long delays in receiving feedback, especially when optimizing for some long-term metrics. While mitigating the effects of delays in learning i…