Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/76295
Type: Artigo de periódico
Title: A new matrix-free algorithm for the large-scale trust-region subproblem
Author: Rojas, M
Santos, SA
Sorensen, DC
Abstract: We present a new method for the large-scale trust-region subproblem. The method is matrix-free in the sense that only matrix-vector products are required. We recast the trust-region subproblem as a parameterized eigenvalue problem and compute an optimal value for the parameter. We then nd the solution of the trust-region subproblem from the eigenvectors associated with two of the smallest eigenvalues of the parameterized eigenvalue problem corresponding to the optimal parameter. The new algorithm uses a different interpolating scheme than existing methods and introduces a uni ed iteration that naturally includes the so-called hard case. We show that the new iteration is well defined and convergent at a superlinear rate. We present computational results to illustrate convergence properties and robustness of the method.
Subject: regularization
constrained quadratic optimization
trust region
Lanczos method
Country: EUA
Editor: Siam Publications
Rights: aberto
Identifier DOI: 10.1137/S105262349928887X
Date Issue: 2001
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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