Proximal Algorithms for a class of abstract convex functions
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866914694386679808 |
|---|---|
| author | Bednarczuk, Ewa Lorenz, Dirk Tran, The Hung |
| author_facet | Bednarczuk, Ewa Lorenz, Dirk Tran, The Hung |
| contents | In this paper we analyze a class of nonconvex optimization problem from the viewpoint of abstract convexity. Using the respective generalizations of the subgradient we propose an abstract notion proximal operator and derive a number of algorithms, namely an abstract proximal point method, an abstract forward-backward method and an abstract projected subgradient method. Global convergence results for all algorithms are discussed and numerical examples are given |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_17072 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Proximal Algorithms for a class of abstract convex functions Bednarczuk, Ewa Lorenz, Dirk Tran, The Hung Optimization and Control 49J45, 65K05, 74P10, 90C26, In this paper we analyze a class of nonconvex optimization problem from the viewpoint of abstract convexity. Using the respective generalizations of the subgradient we propose an abstract notion proximal operator and derive a number of algorithms, namely an abstract proximal point method, an abstract forward-backward method and an abstract projected subgradient method. Global convergence results for all algorithms are discussed and numerical examples are given |
| title | Proximal Algorithms for a class of abstract convex functions |
| topic | Optimization and Control 49J45, 65K05, 74P10, 90C26, |
| url | https://arxiv.org/abs/2402.17072 |