A block coordinate gradient descent method for regularized convex separable optimization and covariance selection

A block coordinate gradient descent method for regularized convex separable optimization and covariance selection

10.1007/s10107-011-0471-1

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Main Authors: Yun, S., Tseng, P., Toh, K.-C.
Other Authors: MATHEMATICS
Format: Article
Published: 2014
Subjects:
ℓ1- penalization
Block coordinate gradient descent
Complexity
Convex optimization
Covariance selection
Global convergence
Linear rate convergence
Maximum likelihood estimation
Online Access:http://scholarbank.nus.edu.sg/handle/10635/102605
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Institution: National University of Singapore
id sg-nus-scholar.10635-102605
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spelling sg-nus-scholar.10635-1026052023-10-25T22:41:40Z A block coordinate gradient descent method for regularized convex separable optimization and covariance selection Yun, S. Tseng, P. Toh, K.-C. MATHEMATICS ℓ1- penalization Block coordinate gradient descent Complexity Convex optimization Covariance selection Global convergence Linear rate convergence Maximum likelihood estimation 10.1007/s10107-011-0471-1 Mathematical Programming 129 2 331-355 2014-10-28T02:27:36Z 2014-10-28T02:27:36Z 2011-10 Article Yun, S., Tseng, P., Toh, K.-C. (2011-10). A block coordinate gradient descent method for regularized convex separable optimization and covariance selection. Mathematical Programming 129 (2) : 331-355. ScholarBank@NUS Repository. https://doi.org/10.1007/s10107-011-0471-1 00255610 http://scholarbank.nus.edu.sg/handle/10635/102605 000295785000008 Scopus
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
topic ℓ1- penalization
Block coordinate gradient descent
Complexity
Convex optimization
Covariance selection
Global convergence
Linear rate convergence
Maximum likelihood estimation
spellingShingle ℓ1- penalization
Block coordinate gradient descent
Complexity
Convex optimization
Covariance selection
Global convergence
Linear rate convergence
Maximum likelihood estimation
Yun, S.
Tseng, P.
Toh, K.-C.
A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
description 10.1007/s10107-011-0471-1
author2 MATHEMATICS
author_facet MATHEMATICS
Yun, S.
Tseng, P.
Toh, K.-C.
format Article
author Yun, S.
Tseng, P.
Toh, K.-C.
author_sort Yun, S.
title A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
title_short A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
title_full A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
title_fullStr A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
title_full_unstemmed A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
title_sort block coordinate gradient descent method for regularized convex separable optimization and covariance selection
publishDate 2014
url http://scholarbank.nus.edu.sg/handle/10635/102605
_version_ 1781787609584893952

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