Subgradient projection algorithms and approximate solutions of convex feasibility problems
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Publication:364738
DOI10.1007/s10957-012-0238-8zbMath1292.90288OpenAlexW2021769279MaRDI QIDQ364738
Publication date: 9 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/s10957-012-0238-8
Analysis of algorithms (68W40) Nonlinear programming (90C30) Programming in abstract spaces (90C48) Approximation algorithms (68W25)
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Cites Work
- Hilbertian convex feasibility problem: Convergence of projection methods
- Relaxed outer projections, weighted averages and convex feasibility
- A finitely convergent ``row-action method for the convex feasibility problem
- Block-iterative algorithms for solving convex feasibility problems in Hilbert and in Banach spaces
- Convergence theorems for sequences of nonlinear operators in Banach spaces
- Perturbation resilience and superiorization of iterative algorithms
- Row-Action Methods for Huge and Sparse Systems and Their Applications
- Cyclic subgradient projections
- On Projection Algorithms for Solving Convex Feasibility Problems
- Convex Analysis
- The method of projections for finding the common point of convex sets
- Minimization of unsmooth functionals
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