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SDLS: a Matlab package for solving conic least-squares problems

Didier Henrion (henrion***at***laas.fr)
Jérôme Malick (jerome.malick***at***inria.fr)

Abstract: This document is an introduction to the Matlab package SDLS (Semi-Definite Least-Squares) for solving least-squares problems over convex symmetric cones. The package is shortly presented through the addressed problem, a sketch of the implemented algorithm, the syntax and calling sequences, a simple numerical example and some more advanced features. The implemented method consists in solving the dual problem with a quasi-Newton algorithm. We note that SDLS is not the most competitive implementation of this algorithm: efficient, robust, commercial implementations are available (contact the authors). Our main goal with this Matlab SDLS package is to provide a simple, user-friendly software for solving and experimenting with semidefinite least-squares problems. Up to our knowledge, no such freeware exists at this date.

Keywords: semidefinite programming; least-squares problems; convex optimization

Category 1: Optimization Software and Modeling Systems

Category 2: Linear, Cone and Semidefinite Programming (Semi-definite Programming )

Category 3: Convex and Nonsmooth Optimization (Convex Optimization )

Citation: 28 June 2007

Download: [PDF]

Entry Submitted: 09/20/2007
Entry Accepted: 09/20/2007
Entry Last Modified: 10/02/2007

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