A hybrid scaling parameter for the scaled memoryless BFGS method based on the ℓ∞ matrix norm

DOI10.1080/00207160.2018.1465940zbMath1499.90214OpenAlexW2802047615MaRDI QIDQ5031718

Saman Babaie-Kafaki

Publication date: 16 February 2022

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160.2018.1465940

zbMATH Keywords

unconstrained optimizationcondition numberline searchdescent propertyscaled memoryless BFGS update\(\ell_\infty\) norm

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)

Related Items (5)

Nonmonotone diagonally scaled limited-memory BFGS methods with application to compressive sensing based on a penalty model ⋮ An accelerated descent CG algorithm with clustering the eigenvalues for large-scale nonconvex unconstrained optimization and its application in image restoration problems ⋮ A class of new three-term descent conjugate gradient algorithms for large-scale unconstrained optimization and applications to image restoration problems ⋮ Analysis of the maximum magnification by the scaled memoryless DFP updating formula with application to compressive sensing ⋮ Diagonally scaled memoryless quasi-Newton methods with application to compressed sensing

Uses Software

• CUTEr
• SCALCG

Cites Work

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• A modified scaling parameter for the memoryless BFGS updating formula
• Open problems in nonlinear conjugate gradient algorithms for unconstrained optimization
• Convergence analysis of a modified BFGS method on convex minimizations
• On optimality of the parameters of self-scaling memoryless quasi-Newton updating formulae
• A quadratic hybridization of Polak-Ribière-Polyak and Fletcher-Reeves conjugate gradient methods
• Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization
• Accelerated scaled memoryless BFGS preconditioned conjugate gradient algorithm for unconstrained optimization
• Global convergence of BFGS and PRP methods under a modified weak Wolfe-Powell line search
• A modified scaled memoryless BFGS preconditioned conjugate gradient method for unconstrained optimization
• Optimization theory and methods. Nonlinear programming
• Self-Scaling Variable Metric (SSVM) Algorithms
• Self-Scaling Variable Metric (SSVM) Algorithms
• Optimal conditioning of self-scaling variable Metric algorithms
• CUTEr and SifDec
• Benchmarking optimization software with performance profiles.

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