An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization
Many application problems of practical interest can be posed as structured convex optimization models. In this paper, we study a new first-order primaldual algorithm. The method can be easily implementable, provided that the resolvent operators of the component objective functions are simple to eval...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/396753 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850228005949931520 |
|---|---|
| author | Feng Ma Mingfang Ni Lei Zhu Zhanke Yu |
| author_facet | Feng Ma Mingfang Ni Lei Zhu Zhanke Yu |
| author_sort | Feng Ma |
| collection | DOAJ |
| description | Many application problems of practical interest can be posed as structured convex optimization models. In this paper, we study a new first-order primaldual algorithm. The method can be easily implementable, provided that the resolvent operators of the component objective functions are simple to evaluate. We show that the proposed method can be interpreted as a proximal point algorithm with a customized metric proximal parameter. Convergence property is established under the analytic contraction framework. Finally, we verify the efficiency of the algorithm by solving the stable principal component pursuit problem. |
| format | Article |
| id | doaj-art-240b01f60e184136a9c267e04fcd331f |
| institution | OA Journals |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-240b01f60e184136a9c267e04fcd331f2025-08-20T02:04:40ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/396753396753An Implementable First-Order Primal-Dual Algorithm for Structured Convex OptimizationFeng Ma0Mingfang Ni1Lei Zhu2Zhanke Yu3College of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaMany application problems of practical interest can be posed as structured convex optimization models. In this paper, we study a new first-order primaldual algorithm. The method can be easily implementable, provided that the resolvent operators of the component objective functions are simple to evaluate. We show that the proposed method can be interpreted as a proximal point algorithm with a customized metric proximal parameter. Convergence property is established under the analytic contraction framework. Finally, we verify the efficiency of the algorithm by solving the stable principal component pursuit problem.http://dx.doi.org/10.1155/2014/396753 |
| spellingShingle | Feng Ma Mingfang Ni Lei Zhu Zhanke Yu An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization Abstract and Applied Analysis |
| title | An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization |
| title_full | An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization |
| title_fullStr | An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization |
| title_full_unstemmed | An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization |
| title_short | An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization |
| title_sort | implementable first order primal dual algorithm for structured convex optimization |
| url | http://dx.doi.org/10.1155/2014/396753 |
| work_keys_str_mv | AT fengma animplementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT mingfangni animplementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT leizhu animplementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT zhankeyu animplementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT fengma implementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT mingfangni implementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT leizhu implementablefirstorderprimaldualalgorithmforstructuredconvexoptimization AT zhankeyu implementablefirstorderprimaldualalgorithmforstructuredconvexoptimization |