On the String Averaging Method for Sparse Common Fixed Points Problems
Yair Censor,Alexander Segal +1 more
TL;DR: A definition of sparseness of a family of operators is proposed and a string-averaging algorithmic scheme is investigated that favorably handles the common fixed points problem when the family of Operators is sparse.
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About: This article is published in International Transactions in Operational Research. The article was published on 01 Jul 2009. and is currently open access. The article focuses on the topics: Subgradient method & Convex optimization.
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Citations
Algorithms for the Split Variational Inequality Problem
TL;DR: This work proposes a prototypical Split Inverse Problem (SIP) and a new variational problem, called the Split Variational Inequality problem (SVIP), which is a SIP that entails finding a solution of one inverse problem under a given bounded linear transformation.
591
Parallel Optimization: Theory, Algorithms and Applications
TL;DR: Yair Censor and Stavros A. Zenios, Oxford University Press, New York, 1997, 539 pp.
579
The split common fixed-point problem for demicontractive mappings
TL;DR: In this paper, the authors propose the split common fixed point problem, which requires to find a common fixed points of a family of operators in one space whose image under a linear transformation is a shared fixed point of another operator in the image space.
411
Algorithms for the Split Variational Inequality Problem
TL;DR: In this article, the authors propose a split variational inequality problem (SVIP), which is a SIP with the same problem-like structure as the Split Inverse Problem.
Perturbation Resilience and Superiorization of Iterative Algorithms
TL;DR: A methodology is presented whose aim is to produce automatically for an iterative algorithm of the first kind a "superiorized version" of it that retains its computational efficiency but nevertheless goes a long way towards solving an optimization problem.
References
On Projection Algorithms for Solving Convex Feasibility Problems
TL;DR: A very broad and flexible framework is investigated which allows a systematic discussion of questions on behaviour in general Hilbert spaces and on the quality of convergence in convex feasibility problems.
•Book
Uniform Convexity, Hyperbolic Geometry, and Nonexpansive Mappings
Kazimierz Goebel,Simeon Reich +1 more
- 01 Jan 1984
1.6K
Generalized gradients and applications
Abstract: . A theory of generalized gradients for a general class of functions is developed, as well as a corresponding theory of normals to arbitrary closed sets. It is shown how these concepts subsume the usual gradients and normals of smooth functions and manifolds, and the subdifferentials and normals of convex analysis. A theorem is proved concerning the differentiability properties of a function of the form max{g(x, u):u e if}. This result unifies and extends some theorems of Danskin and others. The results are then applied to obtain a characterization of flow-invariant sets which yields theorems of Bony and Brezis as corollaries.
•Book
Parallel Optimization: Theory, Algorithms, and Applications
Yair Censor,Stavros A. Zenios +1 more
- 01 Jan 1997
TL;DR: Foreword Preface Glossary of Symbols 1. Introduction Part I Theory 2. Generalized Distances and Generalized Projections 3. Proximal Minimization with D-Functions Part II Algorithms 4. Penalty Methods, Barrier Methods and Augmented Lagrangians
Parallel Optimization: Theory, Algorithms and Applications
TL;DR: Yair Censor and Stavros A. Zenios, Oxford University Press, New York, 1997, 539 pp.
579