A new gradient projection algorithm for convex minimization problem and its application to split feasibility problem

DOI10.1007/s10013-020-00463-7zbMath1491.47060OpenAlexW3118927758MaRDI QIDQ2054671

Müzeyyen Ertürk, Asiye Kızmaz

Publication date: 3 December 2021

Published in: Vietnam Journal of Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10013-020-00463-7

zbMATH Keywords

weak convergencefixed pointHilbert spaceconvex optimization problemgradient projection algorithmsplit feasibility problem

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Iterative procedures involving nonlinear operators (47J25)

Related Items

Superiorization and bounded perturbation resilience of a gradient projection algorithm solving the convex minimization problem

Cites Work

• A simpler explicit iterative algorithm for a class of variational inequalities in Hilbert spaces
• Hybrid methods with regularization for minimization problems and asymptotically strict pseudocontractive mappings in the intermediate sense
• Averaged mappings and the gradient-projection algorithm
• Perturbed projections and subgradient projections for the multiple-sets split feasibility problem
• Quelques propriétés des opérateurs angle-bornes et n-cycliquement monotones
• A multiprojection algorithm using Bregman projections in a product space
• Convergence of the gradient projection method for generalized convex minimization
• New approximation schemes for general variational inequalities
• New extragradient-type methods for general variational inequalities.
• Strong convergence of a self-adaptive method for the split feasibility problem
• A family of projection gradient methods for solving the multiple-sets split feasibility problem
• Iterative methods for generalized split feasibility problems in Hilbert spaces
• Stability and strong convergence results for random Jungck-Kirk-Noor iterative scheme
• Common fixed points Noor iteration for a finite family of asymptotically quasi-nonexpansive mappings in Banach spaces
• Strong convergence of the CQ method for fixed point iteration processes
• Weak and strong convergence criteria of Noor iterations for asymptotically nonexpansive mappings
• Solving the split feasibility problem without prior knowledge of matrix norms
• The multiple-sets split feasibility problem and its applications for inverse problems
• Global and Asymptotic Convergence Rate Estimates for a Class of Projected Gradient Processes
• On the Linear Convergence of Descent Methods for Convex Essentially Smooth Minimization
• A unified treatment of some iterative algorithms in signal processing and image reconstruction
• Iterative oblique projection onto convex sets and the split feasibility problem
• Solving monotone inclusions via compositions of nonexpansive averaged operators
• Linear convergence of CQ algorithms and applications in gene regulatory network inference
• General iterative methods for equilibrium and constrained convex minimization problem
• Fixed Point Theory for Lipschitzian-type Mappings with Applications
• Convex programming in Hilbert space
• Weak convergence of the sequence of successive approximations for nonexpansive mappings
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