Beta-divergence for Nonnegative Matrix Factorization

Abstract

The beta-divergences has been largely used in the machine learning literature. In this paper, we will go into detail about what they are, where they come from, their relation with Bregman divergence, and why they are so useful in many machine learning algorithms. In particular, Nonnegative Matrix Factorization (NMF), witch we presented as an example using Majorization-Minimization approach.