A framework for analyzing local convergence properties with applications to proximal-point algorithms
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Publication:868573
DOI10.1007/s10957-006-9126-4zbMath1278.90443OpenAlexW2077227317MaRDI QIDQ868573
Publication date: 6 March 2007
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-006-9126-4
inclusionslocal convergencenonisolated solutionsgeneralized equationsupper Lipschitz continuityproximal-point algorithms
Numerical optimization and variational techniques (65K10) Nonsmooth analysis (49J52) Programming in abstract spaces (90C48) Applications of operator theory in optimization, convex analysis, mathematical programming, economics (47N10)
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Cites Work
- Monotone (nonlinear) operators in Hilbert space
- Approximate iterations in Bregman-function-based proximal algorithms
- Local behavior of an iterative framework for generalized equations with nonisolated solutions
- A hybrid approximate extragradient-proximal point algorithm using the enlargement of a maximal monotone operator
- The Proximal Point Algorithm with Genuine Superlinear Convergence for the Monotone Complementarity Problem
- Asymptotic Convergence Analysis of the Proximal Point Algorithm
- Monotone Operators and the Proximal Point Algorithm
- Inexact Variants of the Proximal Point Algorithm without Monotonicity
- Local Convergence of the Proximal Point Algorithm and Multiplier Methods Without Monotonicity
