Probabilistic upper bounds for the matrix two-norm

Research output: Book/ReportReportAcademic

17 Citations (Scopus)
128 Downloads (Pure)

Abstract

We develop probabilistic upper bounds for the matrix two-norm, the largest singular value. These bounds, which are true upper bounds with a user-chosen high probability, are derived with a number of different polynomials that implicitly arise in the Lanczos bidiagonalization process. Since these polynomials are adaptively generated, the bounds typically give very good results. They can be computed efficiently. Together with an approximation that is a guaranteed lower bound, this may result in a small probabilistic interval for the matrix norm of large matrices within a fraction of a second.
Original languageEnglish
Place of PublicationEindhoven
PublisherTechnische Universiteit Eindhoven
Number of pages14
Publication statusPublished - 2013

Publication series

NameCASA-report
Volume1307
ISSN (Print)0926-4507

Fingerprint

Dive into the research topics of 'Probabilistic upper bounds for the matrix two-norm'. Together they form a unique fingerprint.

Cite this