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Algorithm 873: LSTRS: MATLAB Software for Large-Scale Trust-Region Subproblems and Regularization

机译:算法873:LSTRS:用于大规模信任区域子问题和正则化的MATLAB软件

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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.
机译:提出了LSTRS方法的MATLAB 6.0实现。 LSTRS在Rojas等人中描述。 [2000]。 LSTRS设计用于具有一个范数约束的大规模二次问题。该方法基于作为参数化特征值问题的信任区域子问题的重新表述,并且包括为参数找到最佳值的迭代过程。参数的调整需要在每个步骤中解决大规模特征值问题。 LSTRS仅依赖于矩阵向量乘积,具有较低且固定的存储要求,这些特性使其适合于大规模计算。在MATLAB实现中,可以明确指定二次目标函数的Hessian矩阵,也可以矩阵向量乘法例程的形式指定。因此,该实现保留了该方法的无矩阵性质。给出了LSTRS方法和MATLAB软件版本1.2的描述。还包括与该方法的其他技术和应用的比较。提供了使用软件和示例的指南。

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