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Published in:
2018 | OriginalPaper | Chapter
8. Convex Feasibility Problems
Author : Alexander J. Zaslavski
Published in: Algorithms for Solving Common Fixed Point Problems
Publisher: Springer International Publishing
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Abstract
We use inexact subgradient projection algorithms for solving convex feasibility problems. We show that almost all iterates, generated by a perturbed subgradient projection algorithm in a Hilbert space, are approximate solutions. Moreover, we obtain an estimate of the number of iterates which are not approximate solutions.