An analytic theory of shallow networks dynamics for hinge loss classification
An analytic theory of shallow networks dynamics for hinge loss classification
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 to …