swMATH ID: 4729
Software Authors: M. Rojas, S. A. Santos, and D. C. Sorensen
Description: Algorithm 873: LSTRS: MATLAB software for large-scale trust-region subproblems and regularization A MATLAB 6.0 implementation of the LSTRS method is presented. LSTRS was described in Rojas et al. [2000]. 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.
Homepage: http://dl.acm.org/citation.cfm?id=1326553
Dependencies: Matlab
Related Software: GQTPAR; HSL-VF05; ARPACK; GALAHAD; Regularization tools; CUTEst; JDQZ; JDQR; LAPACK; eigs; LSQR; mftoolbox; L-BFGS; SDPT3; SeDuMi; SparseMatrix; CUTEr; Matlab; IRAM; Manopt
Cited in: 34 Publications

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