Optimization solvers and problem formulations for solving data clustering problems

Title: Optimization solvers and problem formulations for solving data clustering problems
Creator: Ugon, Julien
Date: 2007
Type: Text; Journal article
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/32895
Identifier: vital:897
Identifier: ISSN:1348-9151
Abstract: A popular apprach for solving complex optimization problems is through relaxation: some constraints are removed in order to have a convex problem approximating the original problem. On the other hand, direct approaches for solving such problems are becoming increasingly powerful. This paper examines two cases drawn from data analysis, in order to compare the two techniques.; C1
Publisher: Yokohama, Japan Yokohama Publishers
Relation: Pacific Journal of Optimization Vol. 3, no. 2 (2007), p. 387-397
Rights: Copyright Yokohama Publishers
Rights: This metadata is freely available under a CCO license
Subject: 0103 Numerical and Computational Mathematics; Global optimization; Nonconvex; Relaxation
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