On relaxed and contraction-proximal point algorithms in Hilbert spaces

DOI10.1186/1029-242X-2011-41zbMath1267.47106OpenAlexW2136087565WikidataQ59269218 ScholiaQ59269218MaRDI QIDQ352262

Feng Hui Wang, Shu-Yu Wang

Publication date: 4 July 2013

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

Full work available at URL: https://doi.org/10.1186/1029-242x-2011-41

zbMATH Keywords

maximal monotone operatorproximal point algorithmfirmly nonexpansive operator

Mathematics Subject Classification ID

Convex programming (90C25) Monotone operators and generalizations (47H05) Iterative procedures involving nonlinear operators (47J25) Contraction-type mappings, nonexpansive mappings, (A)-proper mappings, etc. (47H09)

Related Items (1)

Convergence results for the zero-finding problem and fixed points of nonexpansive semigroups and strict pseudocontractions

Cites Work

• A note on the regularized proximal point algorithm
• On convergence criteria of generalized proximal point algorithms
• On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
• Approximating fixed points of nonexpansive mappings by the Ishikawa iteration process
• 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
• A Weak-to-Strong Convergence Principle for Fejér-Monotone Methods in Hilbert Spaces
• A new accuracy criterion for approximate proximal point algorithms

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