Complexity of Predictive Neural Networks

Abstract

We announce some general bounds on the interactions of neural and information complexities of feedforward neural networks using general classes of activation functions. We show that, up to constant factors, neural and information complexities combine in a well-defined way in the determination of the complexity of a network.