An online condition number query system

Dianwei Han, Shuting Xu, Jun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Condition number of a matrix is an important measure in numerical analysis and linear algebra. It is a measure of stability or sensitivity of a matrix to numerical operations. However, the direct computation of the condition number of a matrix is very expensive in terms of CPU and memory cost, and becomes prohibitive for large size matrices. We propose to use data mining techniques to estimate the condition number of a given sparse matrix. In particular, we will use Support Vector Machine (SVM) to predict the condition numbers. That is, after computing the sparsity pattern features of a matrix, we use support vector regression (SVR) to predict its condition number. This Online Condition Number Query System (OCNQS) allows the users to submit their matrices and to obtain predicted condition numbers for their matrices. The accuracy of our prediction methods may not be as precise as the direct computation methods, but it is much faster. Our online system accepts matrices in Harwell-Boeing (HB) format and in standard MATLAB format. The users can use our system to estimate the condition number of their matrices through LAPACK software as well.

Original languageEnglish
Title of host publicationProceedings of the 46th Annual Southeast Regional Conference on XX, ACM-SE 46
Pages264-267
Number of pages4
DOIs
StatePublished - 2008
Event46th Annual Southeast Regional Conference on XX, ACM-SE 46 - Auburn, AL, United States
Duration: Mar 28 2009Mar 29 2009

Publication series

NameProceedings of the 46th Annual Southeast Regional Conference on XX, ACM-SE 46

Conference

Conference46th Annual Southeast Regional Conference on XX, ACM-SE 46
Country/TerritoryUnited States
CityAuburn, AL
Period3/28/093/29/09

Keywords

  • ACM proceedings
  • Condition number
  • Data mining
  • Features of matrices

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Hardware and Architecture
  • Software

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