Convergence of the generalized contraction-proximal point algorithm in a Hilbert space

DOI10.1080/02331934.2013.798320zbMath1310.47105OpenAlexW2019073496MaRDI QIDQ5248197

Huanhuan Cui, Feng Hui Wang

Publication date: 28 April 2015

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2013.798320

zbMATH Keywords

strong convergencemaximal monotone operatorproximal point algorithmfirmly nonexpansive operator

Mathematics Subject Classification ID

Convex programming (90C25) Monotone operators and generalizations (47H05) Iterative procedures involving nonlinear operators (47J25) Numerical solutions to equations with nonlinear operators (65J15)

Related Items

The generalized contraction proximal point algorithm with square-summable errors ⋮ The viscosity approximation forward-backward splitting method for zeros of the sum of monotone operators ⋮ Iterative methods for a class of variational inequalities in Hilbert spaces ⋮ Forward-backward splitting algorithm for fixed point problems and zeros of the sum of monotone operators ⋮ A generalized contraction proximal point algorithm with two monotone operators ⋮ Unnamed Item

Cites Work

• A note on the regularized proximal point algorithm
• A proximal point algorithm converging strongly for general errors
• Four parameter proximal point algorithms
• On convergence criteria of generalized proximal point algorithms
• Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization
• On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
• 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
• Operator-Splitting Methods for Monotone Affine Variational Inequalities, with a Parallel Application to Optimal Control

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