# Introduction to Nonnegative Matrix Factorization

arXiv: https://arxiv.org/abs/1703.00663 · HTML: https://mlsanity.com/paper/1703.00663/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2017.

## Built on by (most cited first, 2 of 2)

- [An Exterior Method for Nonnegative Matrix Factorization](https://mlsanity.com/paper/2605.19325/) (2026)
- [LILA: Calibration-Free Structured Pruning of Large Language Models via Latent Spectral Geometry](https://mlsanity.com/paper/2609.11163/) (2026)

## Abstract (arXiv)

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.