Adding variables to quasi-newton Hessian approximations
type: Item
instance of: scholarly article
title: Adding variables to quasi-newton Hessian approximations
zbMATH Open document ID: 0595.65071
DOI: 10.1007/BF00940203
published in: Journal of Optimization Theory and Applications
publication date: 1987-01-01T00:00:00Z
review text: The paper examines methods for increasing the dimension of a quasi-Newton approximation to a Hessian matrix when the dimension of the problem is increased. A new method is proposed, and numerical results given to demonstrate the superiority of the new method to existing methods.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 65H10
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 3958603
zbMATH Keywords: quasi-Newton approximation
zbMATH Keywords: Hessian matrix
zbMATH Keywords: numerical results
zbMATH Keywords: quasi- Newton methods
zbMATH Keywords: stepwise nonlinear regression
zbMATH Keywords: reduced gradient methods
author: David F. Shanno
author: Kang Hoh Phua
describes a project that uses: Algorithm 500
MaRDI profile type: Publication
cites work: Large-scale linearly constrained optimization
cites work: An Adaptive Nonlinear Least-Squares Algorithm
cites work: Matrix conditioning and nonlinear optimization
cites work: Self-Scaling Variable Metric (SSVM) Algorithms
full work available at URL: https://doi.org/10.1007/bf00940203
OpenAlex ID: W2023266244
description: scientific article; zbMATH DE number 3958603