Solving stochastic convex feasibility problems in hilbert spaces

DOI10.1080/01630569608816731zbMath0880.65025OpenAlexW1562194676MaRDI QIDQ4354840

Gilbert Crombez

Publication date: 27 October 1997

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630569608816731

zbMATH Keywords

almost common pointexpected-projection methodsstochastic convex feasibility problems

Mathematics Subject Classification ID

General theory of numerical analysis in abstract spaces (65J05) Hilbert and pre-Hilbert spaces: geometry and topology (including spaces with semidefinite inner product) (46C05) Random operators and equations (aspects of stochastic analysis) (60H25) Probabilistic methods, stochastic differential equations (65C99)

Cites Work

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• Decomposition through formalization in a product space
• Iterations of parallel convex projections in hilbert spaces
• The rate of convergence of dykstra's cyclic projections algorithm: The polyhedral case
• An Adaptive Parallel Projection Method for Solving Convex Feasibility Problems
• Finding projections onto the intersection of convex sets in hilbert spaces
• Viewing Parallel Projection Methods as Sequential Ones in Convex Feasibility Problems
• The method of projections for finding the common point of convex sets

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