Regularized gradient-projection methods for finding the minimum-norm solution of the constrained convex minimization problem

DOI10.1186/s13660-016-1289-4zbMath1357.58024OpenAlexW2568992082WikidataQ41081466 ScholiaQ41081466MaRDI QIDQ504560

Hui-Fang Zhang, Ming Tian

Publication date: 17 January 2017

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/s13660-016-1289-4

zbMATH Keywords

variational inequalityminimum-normregularized gradient-projection methodthe constrained convex minimization problem

Mathematics Subject Classification ID

Contraction-type mappings, nonexpansive mappings, (A)-proper mappings, etc. (47H09) Variational inequalities (global problems) in infinite-dimensional spaces (58E35) Numerical solutions to equations with nonlinear operators (65J15)

Related Items

Gradient projection method with a new step size for the split feasibility problem ⋮ A Sequential Constraint Method for Solving Variational Inequality over the Intersection of Fixed Point Sets ⋮ On solving of constrained convex minimize problem using gradient projection method ⋮ Approximation for the complete elliptic integral of the first kind ⋮ Inertial Haugazeau's hybrid subgradient extragradient algorithm for variational inequality problems in Banach spaces

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