The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf
.
Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence
[article]
2012
arXiv
pre-print
This paper addresses the estimation of the latent dimensionality in nonnegative matrix factorization (NMF) with the \beta-divergence. The \beta-divergence is a family of cost functions that includes the squared Euclidean distance, Kullback-Leibler and Itakura-Saito divergences as special cases. Learning the model order is important as it is necessary to strike the right balance between data fidelity and overfitting. We propose a Bayesian model based on automatic relevance determination in which
arXiv:1111.6085v3
fatcat:fkjooflehfhzldy6qawfpp5n7q