Inexact Version of Bregman Proximal Gradient Algorithm
The Bregman Proximal Gradient (BPG) algorithm is an algorithm for minimizing the sum of two convex functions, with one being nonsmooth. The supercoercivity of the objective function is necessary for the convergence of this algorithm precluding its use in many applications. In this paper, we give an...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2020/1963980 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849406903006789632 |
|---|---|
| author | S. Kabbadj |
| author_facet | S. Kabbadj |
| author_sort | S. Kabbadj |
| collection | DOAJ |
| description | The Bregman Proximal Gradient (BPG) algorithm is an algorithm for minimizing the sum of two convex functions, with one being nonsmooth. The supercoercivity of the objective function is necessary for the convergence of this algorithm precluding its use in many applications. In this paper, we give an inexact version of the BPG algorithm while circumventing the condition of supercoercivity by replacing it with a simple condition on the parameters of the problem. Our study covers the existing results, while giving other. |
| format | Article |
| id | doaj-art-463c4e8a07e4417f8af2f114711102bc |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-463c4e8a07e4417f8af2f114711102bc2025-08-20T03:36:14ZengWileyAbstract and Applied Analysis1085-33751687-04092020-01-01202010.1155/2020/19639801963980Inexact Version of Bregman Proximal Gradient AlgorithmS. Kabbadj0Department of Mathematics, Faculty of Sciences of Meknes, B.P. 11201, Meknes, MoroccoThe Bregman Proximal Gradient (BPG) algorithm is an algorithm for minimizing the sum of two convex functions, with one being nonsmooth. The supercoercivity of the objective function is necessary for the convergence of this algorithm precluding its use in many applications. In this paper, we give an inexact version of the BPG algorithm while circumventing the condition of supercoercivity by replacing it with a simple condition on the parameters of the problem. Our study covers the existing results, while giving other.http://dx.doi.org/10.1155/2020/1963980 |
| spellingShingle | S. Kabbadj Inexact Version of Bregman Proximal Gradient Algorithm Abstract and Applied Analysis |
| title | Inexact Version of Bregman Proximal Gradient Algorithm |
| title_full | Inexact Version of Bregman Proximal Gradient Algorithm |
| title_fullStr | Inexact Version of Bregman Proximal Gradient Algorithm |
| title_full_unstemmed | Inexact Version of Bregman Proximal Gradient Algorithm |
| title_short | Inexact Version of Bregman Proximal Gradient Algorithm |
| title_sort | inexact version of bregman proximal gradient algorithm |
| url | http://dx.doi.org/10.1155/2020/1963980 |
| work_keys_str_mv | AT skabbadj inexactversionofbregmanproximalgradientalgorithm |