A new structured quasi-Newton algorithm using partial information on Hessian
type: Item
instance of: scholarly article
title: A new structured quasi-Newton algorithm using partial information on Hessian
zbMATH Open document ID: 1190.65094
author: Keyvan Amini
author: Ashraf Ghorbani Rizi
published in: Journal of Computational and Applied Mathematics
publication date: 2010-04-27T00:00:00Z
review text: An unconstrained minimization problem on \(\mathbb{R}^n\) is solved by making use of a new modification of the structured quasi-Newton method with a vector parameter. The method uses both available gradient and function value information on Hessian of the objective function. Local and superlinear convergence of the proposed method is proved.
reviewed by: Karel Zimmermann
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 5702041
zbMATH Keywords: modified quasi-Newton method
zbMATH Keywords: partial information on the Hessian
zbMATH Keywords: superlinear convergence
zbMATH Keywords: Dennis-More condition
MaRDI profile type: Publication
full work available at URL: j.cam.2010.01.044
OpenAlex ID: W2018506570
cites work: Q3702408
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DOI: 10.1016/J.CAM.2010.01.044
description: scientific article; zbMATH DE number 5702041