2026
Mitigating the Curse of Detail: Scaling Arguments for Feature Learning and Sample Complexity
ICLR 2026poster
Two pressing topics in the theory of deep learning are the interpretation of feature learning mechanisms and the determination of implicit bias of networks in the rich regime. Current theories of rich feature learning effects revolve around networks with one or two trainable layers or deep linear ne…