A convex model for nonnegative matrix factorization and dimensionality reduction on physical space
A collaborative convex framework for factoring a data matrix X into a nonnegative product AS , with a sparse coefficient matrix S, is proposed. We restrict the columns of the dictionary matrix A to coincide with certain columns of the data matrix X, thereby guaranteeing a physically meaningf...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 21(2012), 7 vom: 11. Juli, Seite 3239-52
|
|---|
| 1. Verfasser: |
Esser, Ernie
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Möller, Michael,
Osher, Stanley,
Sapiro, Guillermo,
Xin, Jack |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2012
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|
|---|
| Schlagworte: | Journal Article
Research Support, U.S. Gov't, Non-P.H.S. |
|---|