Name
Abstract | ||
|---|---|---|
Since Non-negative Matrix Factorization (NMF) was first proposed over a decade ago, it has attracted much attention, particularly
when applied to numerous data analysis problems. Most of the existing algorithms for NMF are based on multiplicative iterative
and alternating least squares algorithms. However, algorithms based on the optimization method are few, especially in the
case where two variables are derived at the same time. In this paper, we propose a non-monotone projection gradient method
for NMF and establish the convergence results of our algorithm. Experimental results show that our algorithm converges to
better solutions than popular multiplicative update-based algorithms. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s10589-010-9387-6 | Computational Optimization and Applications |
Keywords | Field | DocType |
Non-negative Matrix Factorization,Projection gradient,Non-monotone technique | Gradient method,Convergence (routing),Mathematical optimization,Multiplicative function,Matrix decomposition,Non-negative matrix factorization,Alternating least squares,Mathematics,Monotone polygon | Journal |
Volume | Issue | ISSN |
51 | 3 | 0926-6003 |
Citations | PageRank | References |
1 | 0.36 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangli Li | 1 | 24 | 5.55 |
| Hongwei Liu | 2 | 78 | 12.29 |
| Xiuyun Zheng | 3 | 17 | 5.42 |