Primal-Dual algorithms for Abstract convex functions with respect to quadratic functions
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866915722481893376 |
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| author | Bednarczuk, Ewa Tran, The Hung |
| author_facet | Bednarczuk, Ewa Tran, The Hung |
| contents | We consider the saddle point problem where the objective functions are abstract convex with respect to the class of quadratic functions. We propose primal-dual algorithms using the corresponding abstract proximal operator and investigate the convergence under certain restrictions. We test our algorithms by several numerical examples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_07076 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Primal-Dual algorithms for Abstract convex functions with respect to quadratic functions Bednarczuk, Ewa Tran, The Hung Optimization and Control Numerical Analysis We consider the saddle point problem where the objective functions are abstract convex with respect to the class of quadratic functions. We propose primal-dual algorithms using the corresponding abstract proximal operator and investigate the convergence under certain restrictions. We test our algorithms by several numerical examples. |
| title | Primal-Dual algorithms for Abstract convex functions with respect to quadratic functions |
| topic | Optimization and Control Numerical Analysis |
| url | https://arxiv.org/abs/2601.07076 |