Passive and Active Multi-Task Representation Learning

Representation learning has been widely used in many applications. In this talk, I will present our work which uncovers when and why representation learning provably improves the sample efficiency, from a statistical learning point of view. Furthermore, I will talk about how to actively select the most relevant task to boost the performance.

Relevant papers: https://arxiv.org/abs/2202.00911 https://arxiv.org/abs/2002.09434