Name
Title | ||
|---|---|---|
Solving non-negative matrix factorization by alternating least squares with a modified strategy |
Abstract | ||
|---|---|---|
Non-negative matrix factorization (NMF) is a method to obtain a representation of data using non-negativity constraints. A popular approach is alternating non-negative least squares (ANLS). As is well known, if the sequence generated by ANLS has at least one limit point, then the limit point is a stationary point of NMF. However, no evdience has shown that the sequence generated by ANLS has at least one limit point. In order to overcome this shortcoming, we propose a modified strategy for ANLS in this paper. The modified strategy can ensure the sequence generated by ANLS has at least one limit point, and this limit point is a stationary point of NMF. The results of numerical experiments are reported to show the effectiveness of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s10618-012-0265-y | Data Min. Knowl. Discov. |
Keywords | Field | DocType |
Non-negative matrix factorization,Alternating non-negative least squares | Least squares,Data mining,Applied mathematics,Computer science,Matrix decomposition,Non-negative matrix factorization,Alternating least squares | Journal |
Volume | Issue | ISSN |
26 | 3 | 1384-5810 |
Citations | PageRank | References |
3 | 0.38 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongwei Liu | 1 | 78 | 12.29 |
| Xiangli Li | 2 | 24 | 5.55 |
| Xiuyun Zheng | 3 | 17 | 5.42 |