Applying statistical learning theory to deep learning

arXiv:2311.15404v2 Announce Type: replace
Abstract: Although statistical learning theory provides a robust framework to understand supervised learning, many theoretical aspects of deep learning remain unclear, in particular how different architectures may lead to inductive bias when trained using gradient based methods. The goal of these lectures is to provide an overview of some of the main questions that arise when attempting to understand deep learning from a learning theory perspective. After a brief reminder on statistical learning theory and stochastic …

abstract architectures arxiv bias cond-mat.dis-nn cs.lg deep learning framework gradient inductive overview robust statistical stat.ml supervised learning theory type