Properties of a class of preconditioners for weighted least squares problems

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dc.contributor.authorBaryamureeba, Venansius
dc.contributor.authorSteihaug, Trond
dc.contributor.authorZhan, Yin
dc.date.accessioned2022-07-12T11:53:18Z
dc.date.available2022-07-12T11:53:18Z
dc.date.issued1999
dc.description.abstractA sequence of weighted linear least squares problems arises from interior-point methods for linear programming where the changes from one problem to the next are the weights and the right hand side One approach for solving such a weighted linear least squares problem is to apply a preconditioned conjugate gradient method to the normal equations where the preconditioner is based on a low rank correction to the Cholesky factorization of a previous coefficient matrix In this paper, we establish theoretical results for such preconditioners that provide guidelines for the construction of preconditioners of this kind We also present preliminary numerical experiments to validate our theoretical results and to demonstrate the effectiveness of this approachen_US
dc.identifier.citationBaryamureeba, V., Steihaug, T., & Zhang, Y. (1999). Properties of a class of preconditioners for weighted least squares problems.en_US
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/4205
dc.language.isoenen_US
dc.publisherUniversity of Bergen_US
dc.subjectWeighted linear least squaresen_US
dc.subjectPreconditioneren_US
dc.subjectPreconditioned conjugate gradient methoden_US
dc.subjectLinear programmingen_US
dc.subjectInterior-point algorithmsen_US
dc.titleProperties of a class of preconditioners for weighted least squares problemsen_US
dc.typeTechnical Reporten_US
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