A Two-Point Step Size Gradient method forNon-negative Matrix Factorization

摘要：

Nonnegative Matrix Factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. There are many methods for NMF, such as multiplicative iterative and alternating nonnegative data least squares algorithms (ANLS). Among these methods, the most effective way is alternating nonnegative data least squares algorithms. In this paper, we propose a two-point step size gradient method to solve subproblems of ANLS. The numerical experiment shows that our algorithm is much more efficient than some existing algorithms.

关键词： Nonnegative matrix factorization two-point step size gradient method Nonnegative data

作者: Xiaopeng Zhao Hongwei Liu Tongqi Zhang

作者单位: Department of Mathematics, Weinan Teachers College, Weinan, China Department of Mathematics, Xidian Department of Mathematics, Xidian University, Xian, China Department of Mathematics, Weinan Teachers College, Weinan, China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 1080-1083

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）