CSpace  > 计算数学与科学工程计算研究所
On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming
Liu, Ya-Feng1; Liu, Xin2,3; Ma, Shiqian4
2019-05-01
Source PublicationMATHEMATICS OF OPERATIONS RESEARCH
ISSN0364-765X
Volume44Issue:2Pages:632-650
AbstractIn this paper, we consider the linearly constrained composite convex optimization problem, whose objective is a sum of a smooth function and a possibly nonsmooth function. We propose an inexact augmented Lagrangian (IAL) framework for solving the problem. The stopping criterion used in solving the augmented Lagrangian subproblem in the proposed IAL framework is weaker and potentially much easier to check than the one used in most of the existing IAL frameworks/methods. We analyze the global convergence and the nonergodic convergence rate of the proposed IAL framework. Preliminary numerical results are presented to show the efficiency of the proposed IAL framework and the importance of the nonergodic convergence and convergence rate analysis.
Keywordinexact augmented Lagrangian framework nonergodic convergence rate composite convex programming
DOI10.1287/moor.2018.0939
Language英语
Funding ProjectNational Natural Science Foundation of China (NSFC)[11631013] ; National Natural Science Foundation of China (NSFC)[11331012] ; National Natural Science Foundation of China (NSFC)[11671419] ; National Natural Science Foundation of China (NSFC)[11571221] ; Beijing Natural Science Foundation[L172020] ; NSFC[11622112] ; NSFC[11471325] ; NSFC[91530204] ; NSFC[11688101] ; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences (CAS) ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SYS010] ; Department of Mathematics at University of California, Davis
WOS Research AreaOperations Research & Management Science ; Mathematics
WOS SubjectOperations Research & Management Science ; Mathematics, Applied
WOS IDWOS:000468403700011
PublisherINFORMS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/34719
Collection计算数学与科学工程计算研究所
Corresponding AuthorLiu, Ya-Feng
Affiliation1.Chinese Acad Sci, State Key Lab Sci & Engn Comp, Inst Computat Math & Sci Engn Comp, Acad Math & Syst Sci, Beijing, Peoples R China
2.Chinese Acad Sci, State Key Lab Sci & Engn Comp, Acad Math & Syst Sci, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Univ Calif Davis, Dept Math, Davis, CA 95616 USA
Recommended Citation
GB/T 7714
Liu, Ya-Feng,Liu, Xin,Ma, Shiqian. On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming[J]. MATHEMATICS OF OPERATIONS RESEARCH,2019,44(2):632-650.
APA Liu, Ya-Feng,Liu, Xin,&Ma, Shiqian.(2019).On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming.MATHEMATICS OF OPERATIONS RESEARCH,44(2),632-650.
MLA Liu, Ya-Feng,et al."On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming".MATHEMATICS OF OPERATIONS RESEARCH 44.2(2019):632-650.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Liu, Ya-Feng]'s Articles
[Liu, Xin]'s Articles
[Ma, Shiqian]'s Articles
Baidu academic
Similar articles in Baidu academic
[Liu, Ya-Feng]'s Articles
[Liu, Xin]'s Articles
[Ma, Shiqian]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Liu, Ya-Feng]'s Articles
[Liu, Xin]'s Articles
[Ma, Shiqian]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.