On the Successive Projections Approach to Least-Squares Problems

dc.contributor.authorDennis, J.E. Jr.en_US
dc.contributor.authorSteihaug, Tronden_US
dc.date.accessioned2018-06-18T17:23:12Zen_US
dc.date.available2018-06-18T17:23:12Zen_US
dc.date.issued1983-08en_US
dc.date.noteAugust 1983en_US
dc.description.abstractIn this paper, we suggest a generalized Gauss-Seidel approach to sparse linear and nonlinear least-squares problems. The algorithm, closely related to one given by Elfving (1980), uses the work of Curtis, Powell, and Reid (1974) as extended by Coleman and Moré (1983) to divide the variables into nondisjoint groups of structurally orthogonal columns and then projects the updated residual into each column subspace of the Jacobian in turn. In the linear case, this procedure can be viewed as an alternate ordering of the variables in the Gauss-Seidel method. Preliminary tests indicate that this leads quickly to cheap solutions of limited accuracy for linear problems, and that this approach is promising for an inexact Gauss-Newton analog of the inexact Newton approach of Dembo, Eisenstat, and Steihaug (1981).en_US
dc.format.extent29 ppen_US
dc.identifier.citationDennis, J.E. Jr. and Steihaug, Trond. "On the Successive Projections Approach to Least-Squares Problems." (1983) <a href="https://hdl.handle.net/1911/101559">https://hdl.handle.net/1911/101559</a>.en_US
dc.identifier.digitalTR83-18en_US
dc.identifier.urihttps://hdl.handle.net/1911/101559en_US
dc.language.isoengen_US
dc.titleOn the Successive Projections Approach to Least-Squares Problemsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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