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|Type:||Artigo de periódico|
|Title:||Algorithm 873: LSTRS: MATLAB software for large-scale trust-region subproblems and regularization|
|Abstract:||A MATLAB 6.0 implementation of the LSTRS method is presented. LSTRS was described in Rojas et al. . LSTRS is designed for large-scale quadratic problems with one norm constraint. The method is based on a reformulation of the trust-region subproblem as a parameterized eigenvalue problem, and consists of an iterative procedure that finds the optimal value for the parameter. The adjustment of the parameter requires the solution of a large-scale eigenvalue problem at each step. LSTRS relies on matrix-vector products only and has low and fixed storage requirements, features that make it suitable for large-scale computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function can be specified either explicitly, or in the form of a matrix-vector multiplication routine. Therefore, the implementation preserves the matrix-free nature of the method. A description of the LSTRS method and of the MATLAB software, version 1.2, is presented. Comparisons with other techniques and applications of the method are also included. A guide for using the software and examples are provided.|
|Editor:||Assoc Computing Machinery|
|Citation:||Acm Transactions On Mathematical Software. Assoc Computing Machinery, v. 34, n. 2, 2008.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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