Reviews: The committee machine: Computational to statistical gaps in learning a two-layers neural network

The committee machine is a simple and natural model for a 2-layer neural network. The results of the paper also apply to many related models: you are allowed an arbitrary function mapping the K hidden values to the final binary output.) This paper studies the problem of learning the weights W under a natural random model. We are given m random examples (X,Y) where the input X (in R n) is iid Gaussian and Y (in { 1,-1}) is the associated output of the network. The unknown weights W are iid from a known prior.