文件名称：Projected Gradient Methods for Non-negative Matrix Factorization
文件大小：373KB
文件格式：PDF
更新时间：2018-04-28 07:46:08
Projected Gradient NMF
Projected Gradient Methods for Non-negative Matrix Factorization Chih-Jen Lin Department of Computer Science Abstract Non-negative matrix factorization (NMF) can be formulated as a minimization problem with bound constraints. Although bound-constrained optimization has been studied extensively in both theory and practice, so far no study has formally applied its techniques to NMF. In this paper, we propose two projected gradient methods for NMF, both of which exhibit strong optimization properties. We discuss ecient implementations and demonstrate that one of the proposed methods converges faster than the popular multiplicative update approach. A simple MATLAB code is also provided.