Error sensitivity for strongly convergent modifications of the proximal point algorithm

DOI10.1007/s10957-015-0835-4zbMath1345.47052OpenAlexW1939526422MaRDI QIDQ283935

Hong-Kun Xu, Yamin Wang, Feng Hui Wang

Publication date: 17 May 2016

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

Full work available at URL: https://doi.org/10.1007/s10957-015-0835-4

zbMATH Keywords

resolventstrong convergencemaximal monotone operatorproximal point algorithmcontraction-proximal point algorithm

Mathematics Subject Classification ID

Convex programming (90C25) Monotone operators and generalizations (47H05) Iterative procedures involving nonlinear operators (47J25) Numerical methods for variational inequalities and related problems (65K15)

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Convergence of over-relaxed contraction-proximal point algorithm in Hilbert spaces ⋮ Iterative method with inertial terms for nonexpansive mappings: applications to compressed sensing ⋮ Strong convergence of regularized new proximal point algorithms ⋮ Strong convergence of the forward–backward splitting method with multiple parameters in Hilbert spaces ⋮ Quantitative results on a Halpern-type proximal point algorithm ⋮ Strong convergence of over-relaxed multi-parameter proximal scaled gradient algorithm and superiorization ⋮ A generalized contraction proximal point algorithm with two monotone operators ⋮ Unnamed Item ⋮ The split feasibility problem with multiple output sets for demicontractive mappings

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• Monotone Operators and the Proximal Point Algorithm
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• A new accuracy criterion for approximate proximal point algorithms

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