Name: Uniqueness of Non-Negative Matrix Factorization
Creator: Laurberg, Hans
Keywords: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

descriptionPublicationkeyboard_double_arrow_right Article , Contribution for newspaper or weekly magazine , Other literature type 01 Aug 2007Publisher:IEEEJournal:2007 IEEE/SP 14th Workshop on Statistical Signal Processing

Authors: Laurberg, Hans;

doi: 10.1109/ssp.2007.4301215

Uniqueness of Non-Negative Matrix Factorization

- Summary
- Metrics

Abstract

In this paper, two new properties of stochastic vectors are introduced and a strong uniqueness theorem on non-negative matrix factorizations (NMF) is introduced. It is described how the theorem can be applied to two of the common application areas of NMF, namely music analysis and probabilistic latent semantic analysis. Additionally, the theorem can be used for selecting the model order and the sparsity parameter in sparse NMFs.

Related Organizations

Aalborg University Library (AUB)
Denmark
Aalborg University
Denmark

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	16
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%