An Efficient Subspace Minimization Conjugate Gradient Method for Solving Nonlinear Monotone Equations with Convex Constraints

The subspace minimization conjugate gradient (SMCG) methods proposed by Yuan and Store are efficient iterative methods for unconstrained optimization, where the search directions are generated by minimizing the quadratic approximate models of the objective function at the current iterative point. Al...

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Autori principali:	Taiyong Song, Zexian Liu
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2024-03-01
Serie:	Axioms
Soggetti:	nonlinear monotone equations subspace minimization conjugate gradient method convex constraints global convergence R-linear convergence rate
Accesso online:	https://www.mdpi.com/2075-1680/13/3/170
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