BUIR logo
Communities & Collections
All of BUIR
  • English
  • Türkçe
Log In
Please note that log in via username/password is only available to Repository staff.
Have you forgotten your password?
  1. Home
  2. Browse by Subject

Browsing by Subject "Condition estimation Newton iteration factorization update"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • No Thumbnail Available
    ItemOpen Access
    Bound constrained quadratic programming via piecewise quadratic functions
    (Springer-Verlag, 1999) Madsen, K.; Nielsen, H. B.; Pınar, M. Ç.
    We consider the strictly convex quadratic programming problem with bounded variables. A dual problem is derived using Lagrange duality. The dual problem is the minimization of an unconstrained, piecewise quadratic function. It involves a lower bound of λ1 , the smallest eigenvalue of a symmetric, positive definite matrix, and is solved by Newton iteration with line search. The paper describes the algorithm and its implementation including estimation of λ1, how to get a good starting point for the iteration, and up- and downdating of Cholesky factorization. Results of extensive testing and comparison with other methods for constrained QP are given. © Springer-Verlag 1999.

About the University

  • Academics
  • Research
  • Library
  • Students
  • Stars
  • Moodle
  • WebMail

Using the Library

  • Collections overview
  • Borrow, renew, return
  • Connect from off campus
  • Interlibrary loan
  • Hours
  • Plan
  • Intranet (Staff Only)

Research Tools

  • EndNote
  • Grammarly
  • iThenticate
  • Mango Languages
  • Mendeley
  • Turnitin
  • Show more ..

Contact

  • Bilkent University
  • Main Campus Library
  • Phone: +90(312) 290-1298
  • Email: dspace@bilkent.edu.tr

Bilkent University Library © 2015-2025 BUIR

  • Privacy policy

We collect and process your personal information for the following purposes: Authentication, Preferences, Acknowledgement and Statistics.
To learn more, please read our
privacy policy.

Customize