A fast ADMM algorithm for sparse precision matrix estimation using lasso penalized D-trace loss-Reference-Cited by-同舟云学术

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A fast ADMM algorithm for sparse precision matrix estimation using lasso penalized D-trace loss

Published:2024-03 Issue: Volume:25 Page:100425
ISSN:1110-8665
Container-title:Egyptian Informatics Journal
language:en
Short-container-title:Egyptian Informatics Journal

Author:

Zhu Mingmin,Jiang Jiewei,Gao Weifeng

Funder

National Natural Science Foundation of China

Natural Science Basic Research Program of Shaanxi Province

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Computer Science Applications,Information Systems

Reference39 articles.

1. A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data;Khare;Mach Learn,2019

2. Estimating sparse precision matrices;Padmanabhan;Mon Not R Astron Soc,2016

3. Estimation of covariance and precision matrix, network structure, and a view toward systems biology;Kuismin;Wiley Interdiscip Rev: Comput Stat,2017

4. Sparse methods for biomedical data;Ye;ACM SIGKDD Explor Newsl,2012

5. Improved estimation of the covariance matrix of stock returns with an application to portfolio selection;Ledoit;J Empir Finance,2003

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