Verified Bounds for Least Squares Problems and Underdetermined Linear Systems

  • Authors:
  • Siegfried M. Rump

  • Affiliations:
  • rump@tu-harburg.de

  • Venue:
  • SIAM Journal on Matrix Analysis and Applications
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

New 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.