Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of NRU
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Zhan, Yin"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Properties of a class of preconditioners for weighted least squares problems
    (University of Berg, 1999) Baryamureeba, Venansius; Steihaug, Trond; Zhan, Yin
    A sequence of weighted linear least squares problems arises from interior-point methods for linear programming where the changes from one problem to the next are the weights and the right hand side One approach for solving such a weighted linear least squares problem is to apply a preconditioned conjugate gradient method to the normal equations where the preconditioner is based on a low rank correction to the Cholesky factorization of a previous coefficient matrix In this paper, we establish theoretical results for such preconditioners that provide guidelines for the construction of preconditioners of this kind We also present preliminary numerical experiments to validate our theoretical results and to demonstrate the effectiveness of this approach

Research Dissemination Platform copyright © 2002-2025 NRU

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback