Diagonally scaled memoryless quasi-Newton methods with application to compressed sensing
type: Item
instance of: scholarly article
title: Diagonally scaled memoryless quasi-Newton methods with application to compressed sensing
author: Zohre Aminifard
author: Saman Babaie-Kafaki
published in: Journal of Industrial and Management Optimization
publication date: 2022-10-10T00:00:00Z
Mathematics Subject Classification ID: 90C53
Mathematics Subject Classification ID: 49M37
Mathematics Subject Classification ID: 94A08
zbMATH DE Number: 7599081
zbMATH Keywords: unconstrained optimization
zbMATH Keywords: large-scale optimization
zbMATH Keywords: quasi-Newton update
zbMATH Keywords: scaling
zbMATH Keywords: compressed sensing
describes a project that uses: SCALCG
describes a project that uses: CUTEr
describes a project that uses: CG_DESCENT
MaRDI profile type: Publication
full work available at URL: jimo.2021191
OpenAlex ID: W3215142244
cites work: Numerical expirience with a class of self-scaling quasi-Newton algorithms
cites work: A combined class of self-scaling and modified quasi-Newton methods
cites work: Broyden's quasi-Newton methods for a nonlinear system of equations and unconstrained optimization: a review and open problems
cites work: A robust multi-batch L-BFGS method for machine learning
cites work: A new structured quasi-Newton algorithm using partial information on Hessian
cites work: A modified descent Polak-Ribiére-Polyak conjugate gradient method with global convergence property for nonconvex functions
cites work: An augmented memoryless BFGS method based on a modified secant equation with application to compressed sensing
cites work: Accelerated scaled memoryless BFGS preconditioned conjugate gradient algorithm for unconstrained optimization
cites work: A double-parameter scaling Broyden-Fletcher-Goldfarb-Shanno method based on minimizing the measure function of Byrd and Nocedal for unconstrained optimization
cites work: An extended Dai-Liao conjugate gradient method with global convergence for nonconvex functions
cites work: On optimality of the parameters of self-scaling memoryless quasi-Newton updating formulae
cites work: A modified scaling parameter for the memoryless BFGS updating formula
cites work: A hybrid scaling parameter for the scaled memoryless BFGS method based on the ℓ∞ matrix norm
cites work: Two--parameter scaled memoryless BFGS methods with a nonmonotone choice for the initial step length
cites work: A modified scaled conjugate gradient method with global convergence for nonconvex functions
cites work: A linear hybridization of the Hestenes-Stiefel method and the memoryless BFGS technique
cites work: A descent cautious BFGS method for computing US-eigenvalues of symmetric complex tensors
cites work: Two-Point Step Size Gradient Methods
cites work: Limited memory BFGS method based on a high-order tensor model
cites work: New conjugacy conditions and related nonlinear conjugate gradient methods
cites work: Convergence theory for the structured BFGS secant method with an application to nonlinear least squares
cites work: Benchmarking optimization software with performance profiles.
cites work: A new generalized shrinkage conjugate gradient method for sparse recovery
cites work: Multi-step quasi-Newton methods for optimization
cites work: CUTEr and SifDec
cites work: A Nonmonotone Line Search Technique for Newton’s Method
cites work: Algorithm 851
cites work: A modified BFGS method and its global convergence in nonconvex minimization
cites work: On the global convergence of the BFGS method for nonconvex unconstrained optimization problems
cites work: A modified Hestense–Stiefel conjugate gradient method close to the memoryless BFGS quasi-Newton method
cites work: A descent hybrid conjugate gradient method based on the memoryless BFGS update
cites work: Approximation BFGS methods for nonlinear image restoration
cites work: A particle swarm-BFGS algorithm for nonlinear programming problems
cites work: Q5491447
cites work: Self-Scaling Variable Metric (SSVM) Algorithms
cites work: Optimal conditioning of self-scaling variable Metric algorithms
cites work: Limited memory BFGS algorithm for the matrix approximation problem in Frobenius norm
cites work: Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization
cites work: Optimization theory and methods. Nonlinear programming
cites work: New quasi-Newton methods for unconstrained optimization problems
cites work: The superlinear convergence of a modified BFGS-type method for unconstrained optimization
cites work: A survey of quasi-Newton equations and quasi-Newton methods for optimization
cites work: Broad echo state network for multivariate time series prediction
cites work: A Modified BFGS Algorithm for Unconstrained Optimization
cites work: New quasi-Newton equation and related methods for unconstrained optimization
cites work: A modified BFGS type quasi-Newton method with line search for symmetric nonlinear equations problems
cites work: A nonlinear conjugate gradient method based on the MBFGS secant condition
DOI: 10.3934/JIMO.2021191
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