Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review

Abstract

The paper characterizes classes of functions for which deep learning can be exponentially better than shallow learning. Deep convolutional networks are a special case of these conditions, though weight sharing is not the main reason for their exponential advantage.

Tasks

Reproductions