%ARen, Y.%AZhou, M.%AGe, R.%D2023%I
%K
%MOSTI ID: 10335916
%PMedium: X
%TDepth-Separation with Multilayer Mean-Field Networks
%XMean-field limit has been successfully applied to neural networks, leading to many results in optimizing overparametrized networks. However, existing works often focus on two-layer networks and/or require large number of neurons. We give a new framework for extending the mean-field limit to multilayer network, and show that a polynomial-size three-layer network in our framework can learn the function constructed by Safran et al. (2019) – which is known to be not approximable by any two-layer networks
Country unknown/Code not availableOSTI-MSA