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A hybrid quasi-Newton method with application in sparse recovery (Q2167383)

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Language	Label	Description	Also known as
English	A hybrid quasi-Newton method with application in sparse recovery	scientific article

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scholarly article

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A hybrid quasi-Newton method with application in sparse recovery (English)

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Saman Babaie-Kafaki

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Zohre Aminifard

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Saeide Ghafoori

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Computational and Applied Mathematics

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publication date

25 August 2022

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zbMATH Keywords

unconstrained optimization

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large-scale optimization

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quasi-Newton update

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secant equation

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sparse recovery

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1007/s40314-022-01962-8

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A modified scaled memoryless BFGS preconditioned conjugate gradient method for unconstrained optimization

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On optimality of the parameters of self-scaling memoryless quasi-Newton updating formulae

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A linear hybridization of the Hestenes-Stiefel method and the memoryless BFGS technique

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NESTA: A Fast and Accurate First-Order Method for Sparse Recovery

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CUTEr and SifDec

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Smooth minimization of non-smooth functions

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Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization

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Optimization theory and methods. Nonlinear programming

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New quasi-Newton methods for unconstrained optimization problems

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The superlinear convergence of a modified BFGS-type method for unconstrained optimization

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A survey of quasi-Newton equations and quasi-Newton methods for optimization

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Broad echo state network for multivariate time series prediction

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Convergence analysis of a modified BFGS method on convex minimizations

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A Modified BFGS Algorithm for Unconstrained Optimization

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A nonlinear conjugate gradient method based on the MBFGS secant condition

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Identifiers

10.1007/s40314-022-01962-8

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:2167383

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