Successive element correction algorithms for sparse unconstrained optimization | Zendy

G. Y. Li | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Successive element correction algorithms for sparse unconstrained optimization

Author(s) -

G. Y. Li

Publication year - 1993

Publication title -

journal of optimization theory and applications

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.109

H-Index - 91

eISSN - 1573-2878

pISSN - 0022-3239

DOI - 10.1007/bf00940448

Subject(s) - hessian matrix , theory of computation , algorithm , element (criminal law) , convergence (economics) , mathematics , rate of convergence , mathematical optimization , computer science , key (lock) , computer security , political science , law , economics , economic growth

This paper presents a successive element correction algorithm and a secant modification of this algorithm. The new algorithms are designed to use the gradient evaluations as efficiently as possible in forming the approximate Hessian. The estimates of theq-convergence andr-convergence rates show that the new algorithms may have good local convergence properties. Some restricted numerical results and comparisons with some previously established algorithms suggest that the new algorithms may be efficient in practice.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research