Introduction to Nonnegative Matrix Factorization
It serves as an introductory overview for researchers interested in NMF, with no incremental contributions.
The paper introduces nonnegative matrix factorization (NMF) and provides an overview covering applications like hyperspectral imaging, solution properties, algorithms, and connections to polyhedra, but does not present new results or numbers.
In this paper, we introduce and provide a short overview of nonnegative matrix factorization (NMF). Several aspects of NMF are discussed, namely, the application in hyperspectral imaging, geometry and uniqueness of NMF solutions, complexity, algorithms, and its link with extended formulations of polyhedra. In order to put NMF into perspective, the more general problem class of constrained low-rank matrix approximation problems is first briefly introduced.