About Nonnegative Matrix Factorization: on the posrank approximation

Authors

Abstract

This work addresses the concept of nonnegative matrix factorization (NMF). Some relevant issues for its formulation as as a nonlinear optimization problem will be discussed. The primary goal of NMF
is that of obtaining good quality approximations, namely for video/image visualization. The importance of the rank of the factor matrices and
the use of global optimization techniques is investigated. Some computational experience is reported indicating that, in general, the relation
between the quality of the obtained local minima and the factor matrices dimensions has a strong impact on the quality of the solutions associated
with the decomposition.

Keywords

Signal processing, non negative matrix factorization, feature extraction, dimensionality reduction

Subject

Feature Extraction and Combinatorial Optimization

Conference

Proc Intl Conf on Adaptive and Natural Computing Algorithms, Part II, LNCS 6594, 2011, April 2011