Deep Learning (Partly) Demystified

Abstract

Successes of deep learning are partly due to appropriate selection of activation function, pooling functions, etc. Most of these choices have been made based on empirical comparison and heuristic ideas. In this paper, we show that many of these choices - and the surprising success of deep learning in the first place - can be explained by reasonably simple and natural mathematics.