C-ISTA: Iterative Shrinkage-Thresholding Algorithm for Sparse Covariance Matrix Estimation

doi:10.1109/SSP53291.2023.10207953

	C-ISTA: Iterative Shrinkage-Thresholding Algorithm for Sparse Covariance Matrix Estimation
	Wenfu Xia1 ; Ziping Zhao1 ; Ying Sun 2
	2023-07-02
会议录名称	2023 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP)
ISSN	2373-0803
卷号	2023-July
页码	215-219
发表状态	已发表
DOI	10.1109/SSP53291.2023.10207953
摘要	Covariance matrix estimation is a fundamental task in many fields related to data analysis. As the dimension of the covariance matrix becomes large, it is desirable to obtain a sparse estimator and an efficient algorithm to compute it. In this paper, we consider the covariance matrix estimation problem by minimizing a Gaussian negative log-likelihood loss function with an 1 penalty, which is a constrained non-convex optimization problem. We propose to solve the covariance estimator via a simple iterative shrinkage-thresholding algorithm (C-ISTA) with provable convergence. Numerical simulations with comparison to the benchmark methods demonstrate the computational efficiency and good estimation performance of C-ISTA. © 2023 IEEE.
会议录编者/会议主办者	IEEE ; IEEE Signal Processing Society
关键词	Covariance matrix sparsity iterative shrinkage-thresholding algorithm maximum likelihood non-convex optimization
会议名称	22nd IEEE Statistical Signal Processing Workshop, SSP 2023
会议地点	Hanoi, Vietnam
会议日期	2-5 July 2023
URL	查看原文
收录类别	EI
语种	英语
出版者	IEEE Computer Society
EI入藏号	20233514649917
EI主题词	Covariance matrix
EI分类号	921 Mathematics ; 921.6 Numerical Methods ; 922 Statistical Methods ; 951 Materials Science ; 961 Systems Science
原始文献类型	Conference article (CA)
来源库	IEEE
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/333419
专题	信息科学与技术学院_PI研究组_赵子平组信息科学与技术学院_博士生
作者单位	1.School of Info. Sci. and Tech., ShanghaiTech University, Shanghai, China 2.School of Elec. Eng. and Comp. Sci., The Pennsylvania State University, PA, USA
第一作者单位	上海科技大学
第一作者的第一单位	上海科技大学
推荐引用方式 GB/T 7714	Wenfu Xia,Ziping Zhao,Ying Sun. C-ISTA: Iterative Shrinkage-Thresholding Algorithm for Sparse Covariance Matrix Estimation[C]//IEEE, IEEE Signal Processing Society:IEEE Computer Society,2023:215-219.