An analytic theory of shallow networks dynamics for hinge loss classification*
An analytic theory of shallow networks dynamics for hinge loss classification*
Abstract Neural networks have been shown to perform incredibly well in classification tasks over structured high-dimensional datasets. However, the learning dynamics of such networks is still poorly understood. In this paper we study in detail the training dynamics of a simple type of neural network: a single hidden layer trained …