snigpropertyofmatrixlowrankfactorizationmodel

	snigpropertyofmatrixlowrankfactorizationmodel
	Wang Hong 1; Liu Xin2 ; Chen Xiaojun 1; Yuan Yaxiang 2
	2018
发表期刊	journalofcomputationalmathematics
ISSN	0254-9409
卷号	36 期号:3 页码:374
摘要	Recently, the matrix factorization model attracts increasing attentions in handling large-scale rank minimization problems, which is essentially a nonconvex minimization problem. Specifically, it is a quadratic least squares problem and consequently a quartic polynomial optimization problem. In this paper, we introduce a concept of the SNIG ("Second-order Necessary optimality Implies Global optimality") condition which stands for the property that any second-order stationary point of the matrix factorization model must be a global minimizer. Some scenarios under which the SNIG condition holds are presented. Furthermore, we illustrate by an example when the SNIG condition may fail.
语种	英语
资助项目	[NSFC] ; [China 863 Program] ; [National Center for Mathematics and Interdisciplinary Sciences, CAS] ; [NSFC/Hong Kong Research Grant Council]
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/46795
专题	计算数学与科学工程计算研究所
作者单位	1.香港理工大学 2.中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Wang Hong,Liu Xin,Chen Xiaojun,et al. snigpropertyofmatrixlowrankfactorizationmodel[J]. journalofcomputationalmathematics,2018,36(3):374.
APA	Wang Hong,Liu Xin,Chen Xiaojun,&Yuan Yaxiang.(2018).snigpropertyofmatrixlowrankfactorizationmodel.journalofcomputationalmathematics,36(3),374.
MLA	Wang Hong,et al."snigpropertyofmatrixlowrankfactorizationmodel".journalofcomputationalmathematics 36.3(2018):374.