Linearized two-layers neural networks in high dimension
Linearized two-layers neural networks in high dimension
We consider the problem of learning an unknown function f⋆ on the d-dimensional sphere with respect to the square loss, given i.i.d. samples {(yi,xi)}i≤n where xi is a feature vector uniformly distributed on the sphere and yi=f⋆(xi)+εi. We study two popular classes of models that can be regarded as linearizations …