A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint

Minimizing a sum of Euclidean norms (MSEN) is a classic minimization problem widely used in several applications, including the determination of single and multifacility locations. The objective of the MSEN problem is to find a vector x such that it minimizes a sum of Euclidean norms of systems of e...

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Main Author: Pablo Soto-Quiros
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2022/4838182
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author Pablo Soto-Quiros
author_facet Pablo Soto-Quiros
author_sort Pablo Soto-Quiros
collection DOAJ
description Minimizing a sum of Euclidean norms (MSEN) is a classic minimization problem widely used in several applications, including the determination of single and multifacility locations. The objective of the MSEN problem is to find a vector x such that it minimizes a sum of Euclidean norms of systems of equations. In this paper, we propose a modification of the MSEN problem, which we call the problem of minimizing a sum of squared Euclidean norms with rank constraint, or simply the MSSEN-RC problem. The objective of the MSSEN-RC problem is to obtain a vector x and rank-constrained matrices A1,⋯,Ap such that they minimize a sum of squared Euclidean norms of systems of equations. Additionally, we present an algorithm based on the regularized alternating least-squares (RALS) method for solving the MSSEN-RC problem. We show that given the existence of critical points of the alternating least-squares method, the limit points of the converging sequences of the RALS are the critical points of the objective function. Finally, we show numerical experiments that demonstrate the efficiency of the RALS method.
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spelling doaj-art-11e142ce95c64a4981e8c0c28b8199d72025-02-03T01:20:17ZengWileyJournal of Applied Mathematics1687-00422022-01-01202210.1155/2022/4838182A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank ConstraintPablo Soto-Quiros0Escuela de MatemáticaMinimizing a sum of Euclidean norms (MSEN) is a classic minimization problem widely used in several applications, including the determination of single and multifacility locations. The objective of the MSEN problem is to find a vector x such that it minimizes a sum of Euclidean norms of systems of equations. In this paper, we propose a modification of the MSEN problem, which we call the problem of minimizing a sum of squared Euclidean norms with rank constraint, or simply the MSSEN-RC problem. The objective of the MSSEN-RC problem is to obtain a vector x and rank-constrained matrices A1,⋯,Ap such that they minimize a sum of squared Euclidean norms of systems of equations. Additionally, we present an algorithm based on the regularized alternating least-squares (RALS) method for solving the MSSEN-RC problem. We show that given the existence of critical points of the alternating least-squares method, the limit points of the converging sequences of the RALS are the critical points of the objective function. Finally, we show numerical experiments that demonstrate the efficiency of the RALS method.http://dx.doi.org/10.1155/2022/4838182
spellingShingle Pablo Soto-Quiros
A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint
Journal of Applied Mathematics
title A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint
title_full A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint
title_fullStr A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint
title_full_unstemmed A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint
title_short A Regularized Alternating Least-Squares Method for Minimizing a Sum of Squared Euclidean Norms with Rank Constraint
title_sort regularized alternating least squares method for minimizing a sum of squared euclidean norms with rank constraint
url http://dx.doi.org/10.1155/2022/4838182
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