Numerical Optimization with Computational Errors
Alexander J. Zaslavski ()
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Alexander J. Zaslavski: The Technion – Israel Institute of Techn
in Springer Optimization and Its Applications from Springer, currently edited by Pardalos, Panos, Thai, My T. and Du, Ding-Zhu
Date: 2016
ISBN: 978-3-319-30921-7
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Chapters in this book:
- Ch Chapter 1 Introduction
- Alexander J. Zaslavski
- Ch Chapter 10 Proximal Point Methods in Metric Spaces
- Alexander J. Zaslavski
- Ch Chapter 11 Maximal Monotone Operators and the Proximal Point Algorithm
- Alexander J. Zaslavski
- Ch Chapter 12 The Extragradient Method for Solving Variational Inequalities
- Alexander J. Zaslavski
- Ch Chapter 13 A Common Solution of a Family of Variational Inequalities
- Alexander J. Zaslavski
- Ch Chapter 14 Continuous Subgradient Method
- Alexander J. Zaslavski
- Ch Chapter 15 Penalty Methods
- Alexander J. Zaslavski
- Ch Chapter 16 Newton’s Method
- Alexander J. Zaslavski
- Ch Chapter 2 Subgradient Projection Algorithm
- Alexander J. Zaslavski
- Ch Chapter 3 The Mirror Descent Algorithm
- Alexander J. Zaslavski
- Ch Chapter 4 Gradient Algorithm with a Smooth Objective Function
- Alexander J. Zaslavski
- Ch Chapter 5 An Extension of the Gradient Algorithm
- Alexander J. Zaslavski
- Ch Chapter 6 Weiszfeld’s Method
- Alexander J. Zaslavski
- Ch Chapter 7 The Extragradient Method for Convex Optimization
- Alexander J. Zaslavski
- Ch Chapter 8 A Projected Subgradient Method for Nonsmooth Problems
- Alexander J. Zaslavski
- Ch Chapter 9 Proximal Point Method in Hilbert Spaces
- Alexander J. Zaslavski
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spopap:978-3-319-30921-7
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DOI: 10.1007/978-3-319-30921-7
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