6 papers
A Lasry-Lions envelope approach for mathematical programs with complementarity constraints
Jia Wang, Andreas Themelis, Ivan Markovsky +1
We propose a homotopy method for solving mathematical programs with complementarity constraints (CCs). The indicator function of the CCs is relaxed by the Lasry--Lions double envel…
Linesearch-free adaptive Bregman proximal gradient for convex minimization under local relative smoothness
Hongjia Ou, Puya Latafat, Andreas Themelis
This paper introduces adaptive Bregman proximal gradient algorithms for solving convex composite minimization problems without relying on global relative smoothness or strong conve…
PANOC-lite: A simpler and more efficient algorithm for composite minimization
Alexander Bodard, Pieter Pas, Andreas Themelis +1
This work introduces a simple and efficient linesearch method for composite minimization that accelerates proximal-gradient iterations with fast Newton-type directions. Our algorit…
Bregman level proximal subdifferentials and new characterizations of Bregman proximal operators
Ziyuan Wang, Andreas Themelis
Classic subdifferentials in variational analysis may fail to fully represent the Bregman proximal operator in the absence of convexity. In this paper, we fill this gap by introduci…
On the natural domain of Bregman operators
Andreas Themelis, Ziyuan Wang
The Bregman proximal mapping and Bregman-Moreau envelope are traditionally studied for functions defined on the entire space , even though these constructions depend…
A penalty barrier framework for nonconvex constrained optimization
Alberto De Marchi, Andreas Themelis
We consider minimization problems with structured objective function and smooth constraints, and present a flexible framework that combines the beneficial regularization effects of…