Convex Feasibility Problems

Alexander J. Zaslavski
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Alexander J. Zaslavski: Technion:Israel Institute of Technology

Chapter Chapter 8 in Algorithms for Solving Common Fixed Point Problems, 2018, pp 281-306 from Springer

Abstract: 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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-77437-4_8

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DOI: 10.1007/978-3-319-77437-4_8

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