Primal-Dual algorithms for Abstract convex functions with respect to quadratic functions

arXiv (Cornell University) 2026 Preprint Open access

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Authors: Ewa M. Bednarczuk, The Hung Tran
DOI: 10.48550/arxiv.2601.07076
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Optimization and Variational Analysis Advanced Optimization Algorithms Research Mathematical Inequalities and Applications

Publication details

Journal / source
arXiv (Cornell University)
Publication date
11 January 2026
Document type
Preprint