Inexact Block Coordinate Descent Methods For Symmetric Nonnegative Matrix Factorization.

IEEE Transactions on Signal Processing(2017)

引用 24|浏览41
暂无评分
摘要
Symmetric nonnegative matrix factorization (SNMF) is equivalent to computing a symmetric nonnegative low rank approximation of a data similarity matrix. It inherits the good data interpretability of the well-known nonnegative matrix factorization technique and has better ability of clustering nonlinearly separable data. In this paper, we focus on the algorithmic aspect of the SNMF problem and prop...
更多
查看译文
关键词
Signal processing algorithms,Convergence,Algorithm design and analysis,Clustering algorithms,Symmetric matrices,Approximation algorithms,Linear matrix inequalities
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要