125 citations · 684 across the 34 of their papers we have counts for
39 papers
A Smoothed Augmented Lagrangian Method for Mathematical Programs with Vertical Complementarity Constraints
Jia Wang, Andreas Themelis, Panagiotis Patrinos
We propose a smoothed augmented Lagrangian method (ALM) for solving mathematical programs with vertical complementarity constraints (VCCs). The augmented Lagrangian function involv…
An Adaptive Linesearch-free Method for Monotone Variational Inequalities under Local Lipschitz Continuity
Hongjia Ou, Andreas Themelis, Puya Latafat
The forward-reflected-backward (FRB) splitting solves inclusion problems involving the sum of a maximally monotone operator and a monotone Lipschitz continuous operator. Each itera…
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…
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…
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…
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…