On the strong convergence of Halpern type proximal point algorithm

DOI10.1007/s10957-012-0213-4zbMath1272.90112OpenAlexW2079312367MaRDI QIDQ368740

Hadi Khatibzadeh, Sajad Ranjbar

Publication date: 23 September 2013

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

Full work available at URL: https://doi.org/10.1007/s10957-012-0213-4

zbMATH Keywords

strong convergencemaximal monotone operatorsubdifferentialcoercive operatorHalpern type algorithmproximal-point algorithm

Mathematics Subject Classification ID

Interior-point methods (90C51) Programming in abstract spaces (90C48)

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The generalized contraction proximal point algorithm with square-summable errors ⋮ Convergence analysis of the proximal point algorithm for pseudo-monotone equilibrium problems ⋮ On the weak and strong convergence of the proximal point algorithm in reflexive Banach spaces ⋮ Hybrid proximal point algorithm and applications to equilibrium problems and convex programming ⋮ Strongly convergent inertial proximal point algorithm without on-line rule ⋮ Existence and continuous-discrete asymptotic behaviour for Tikhonov-like dynamical equilibrium systems ⋮ Proximal point algorithm for infinite pseudo-monotone bifunctions ⋮ Quantitative translations for viscosity approximation methods in hyperbolic spaces ⋮ Regularized solution of LCP problems with application to rigid body dynamics

Cites Work

• Some remarks on the proximal point algorithm
• Asymptotic behavior of a discrete nonlinear oscillator with damping dynamical system
• A proximal point algorithm converging strongly for general errors
• Four parameter proximal point algorithms
• Inexact Halpern-type proximal point algorithm
• A regularization method for the proximal point algorithm
• On convergence criteria of generalized proximal point algorithms
• On the proximal point algorithm
• Produits infinis de resolvantes
• Convergence of generalized proximal point algorithms
• Approximating solutions of maximal monotone operators in Hilbert spaces
• On the contraction-proximal point algorithms with multi-parameters
• Iterative Algorithms for Nonlinear Operators
• On the Convergence of the Proximal Point Algorithm for Convex Minimization
• Monotone Operators and the Proximal Point Algorithm
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