collaborators
Showing math.OCShow all

6 papers · 1 filter

math.OC2026

Proximity operator characterization for abstract convex functions

Ewa Bednarczuk, The Hung Tran

We consider proximity operator as a selector of the subgradient in the context of abstract convexity and characterize its properties in term of minimization problems. We also inves…

math.OC2026

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

Ewa Bednarczuk, The Hung Tran

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…

math.OC2024

Primal-dual algorithm for weakly convex functions under sharpness conditions

Ewa Bednarczuk, The Hung Tran, Monika Syga

We investigate the convergence of the primal-dual algorithm for composite optimization problems when the objective functions are weakly convex. We introduce a modified duality gap…

math.OC2024

Outer Approximation Scheme for Weakly Convex Constrained Optimization Problems

Ewa M. Bednarczuk, Giovanni Bruccola, Jean-Christophe Pesquet +1

Outer approximation methods have long been employed to tackle a variety of optimization problems, including linear programming, in the 1960s, and continue to be effective for solvi…

math.OC2024

Forward-Backward algorithms for weakly convex problems

Ewa Bednarczuk, Giovanni Bruccola, Gabriele Scrivanti +1

We investigate the convergence properties of exact and inexact forward-backward algorithms to minimise the sum of two weakly convex functions defined on a Hilbert space, where one…

math.OC2024

Proximal Algorithms for a class of abstract convex functions

Ewa Bednarczuk, Dirk Lorenz, The Hung Tran

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 a…