Learning the parts of objects by non-negative matrix factorization

Daniel D. Lee and H. Sebastian Seung
Additional contact information
Daniel D. Lee: Bell Laboratories, Lucent Technologies
H. Sebastian Seung: Bell Laboratories, Lucent Technologies

Nature, 1999, vol. 401, issue 6755, 788-791

Abstract: Abstract Is perception of the whole based on perception of its parts? There is psychological1 and physiological2,3 evidence for parts-based representations in the brain, and certain computational theories of object recognition rely on such representations4,5. But little is known about how brains or computers might learn the parts of objects. Here we demonstrate an algorithm for non-negative matrix factorization that is able to learn parts of faces and semantic features of text. This is in contrast to other methods, such as principal components analysis and vector quantization, that learn holistic, not parts-based, representations. Non-negative matrix factorization is distinguished from the other methods by its use of non-negativity constraints. These constraints lead to a parts-based representation because they allow only additive, not subtractive, combinations. When non-negative matrix factorization is implemented as a neural network, parts-based representations emerge by virtue of two properties: the firing rates of neurons are never negative and synaptic strengths do not change sign.

Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (243)

Downloads: (external link)
https://www.nature.com/articles/44565 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:401:y:1999:i:6755:d:10.1038_44565

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/44565

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().