Rump, Siegfried M.Siegfried M.Rump2020-11-242020-11-242012-01-13SIAM Journal on Matrix Analysis and Applications 1 (33): 130-148 (2012-06-04)http://hdl.handle.net/11420/7918New algorithms are presented for computing verified error bounds for least squares problems and underdetermined linear systems. In contrast to previous approaches the new methods do not rely on normal equations and are applicable to sparse matrices. Computational results demonstrate that the new methods are faster than existing ones. © 2012 Society for Industrial and Applied Mathematics.en1095-7162SIAM journal on matrix analysis and applications20121130148Soc.Extra-precise residual evaluationINTLABLeast squares problemsNormal equationsUnderdetermined linear systemInformatikMathematikVerified bounds for least squares problems and underdetermined linear systemsJournal Article10.1137/110840248Other