23 citations · 58 across the 14 of their papers we have counts for
18 papers
A comparative numerical study of graph-based splitting algorithms for linear subspaces
Francisco J. Aragón-Artacho, Rubén Campoy, Irene López-Larios +1
In this note, we test the performance of six algorithms from the family of graph-based splitting methods [SIAM J. Optim., 34 (2024), pp. 1569-1594] specialized to normal cones of l…
Nonmonotone subgradient methods based on a local descent lemma
Francisco J. Aragón-Artacho, Rubén Campoy, Pedro Pérez-Aros +1
In this paper we present a nonmonotone line search subgradient algorithm tailored to upper- functions. This is a family of nonsmooth and nonconvex functions that sat…
Graph splitting methods: Fixed points and strong convergence for linear subspaces
Francisco J. Aragón-Artacho, Heinz H. Bauschke, Rubén Campoy +1
In this paper, we develop a general analysis for the fixed points of the operators defining the graph splitting methods from [SIAM J. Optim., 34 (2024), pp. 1569-1594] by Bredies,…
Forward-backward algorithms devised by graphs
Francisco J. Aragón-Artacho, Rubén Campoy, César López-Pastor
In this work, we present a methodology for devising forward-backward methods for finding zeros in the sum of a finite number of maximally monotone operators. We extend the framewor…
Regularity of sets under a reformulation in a product space of reduced dimension
Rubén Campoy
Different notions on regularity of sets and of collection of sets play an important role in the analysis of the convergence of projection algorithms in nonconvex scenarios. While s…
A Product Space Reformulation with Reduced Dimension for Splitting Algorithms
Rubén Campoy
In this paper we propose a product space reformulation to transform monotone inclusions described by finitely many operators on a Hilbert space into equivalent two-operator problem…
An Adaptive Alternating Direction Method of Multipliers
Sedi Bartz, Rubén Campoy, Hung M. Phan
The alternating direction method of multipliers (ADMM) is a powerful splitting algorithm for linearly constrained convex optimization problems. In view of its popularity and applic…
Strengthened Splitting Methods for Computing Resolvents
Francisco J. Aragón Artacho, Rubén Campoy, Matthew K. Tam
In this work, we develop a systematic framework for computing the resolvent of the sum of two or more monotone operators which only activates each operator in the sum individually.…
Demiclosedness principles for generalized nonexpansive mappings
Sedi Bartz, Rubén Campoy, Hung M. Phan
Demiclosedness principles are powerful tools in the study of convergence of iterative methods. For instance, a multi-operator demiclosedness principle for firmly nonexpansive mappi…
The Boosted DC Algorithm for linearly constrained DC programming
Francisco J. Aragón Artacho, Rubén Campoy, Phan T. Vuong
The Boosted Difference of Convex functions Algorithm (BDCA) has been recently introduced to accelerate the performance of the classical Difference of Convex functions Algorithm (DC…
Using positive spanning sets to achieve d-stationarity with the Boosted DC Algorithm
Francisco J. Aragón Artacho, Rubén Campoy, Phan T. Vuong
The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions. A recently proposed accelerated version, termed BDCA for Bo…
The Douglas-Rachford Algorithm for Convex and Nonconvex Feasibility Problems
Francisco J. Aragón Artacho, Rubén Campoy, Matthew K. Tam
The Douglas-Rachford method, a projection algorithm designed to solve continuous optimization problems, forms the basis of a useful heuristic for solving combinatorial optimization…
An enhanced formulation for solving graph coloring problems with the Douglas-Rachford algorithm
F. J. Aragón Artacho, R. Campoy, V. Elser
We study the behavior of the Douglas-Rachford algorithm on the graph vertex-coloring problem. Given a graph and a number of colors, the goal is to find a coloring of the vertices s…
Computing the resolvent of the sum of maximally monotone operators with the averaged alternating modified reflections algorithm
F. J. Aragón Artacho, R. Campoy
The averaged alternating modified reflections algorithm is a projection method for finding the closest point in the intersection of closed convex sets to a given point in a Hilbert…
Optimal rates of linear convergence of the averaged alternating modified reflections method for two subspaces
Francisco J. Aragón Artacho, Rubén Campoy
The averaged alternating modified reflections (AAMR) method is a projection algorithm for finding the closest point in the intersection of convex sets to any arbitrary point in a H…
A feasibility approach for constructing combinatorial designs of circulant type
Francisco J. Aragón Artacho, Rubén Campoy, Ilias Kotsireas +1
In this work, we propose an optimization approach for constructing various classes of circulant combinatorial designs that can be defined in terms of autocorrelations. The problem…
Solving graph coloring problems with the Douglas-Rachford algorithm
Francisco J. Aragón Artacho, Rubén Campoy
We present the Douglas-Rachford algorithm as a successful heuristic for solving graph coloring problems. Given a set of colors, these type of problems consist in assigning a color…
A new projection method for finding the closest point in the intersection of convex sets
Francisco J. Aragón Artacho, Rubén Campoy
In this paper we present a new iterative projection method for finding the closest point in the intersection of convex sets to any arbitrary point in a Hilbert space. This method,…