The Extragradient Method for Convex Optimization

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

Chapter Chapter 7 in Numerical Optimization with Computational Errors, 2016, pp 105-118 from Springer

Abstract: Abstract In this chapter we study convergence of the extragradient method for constrained convex minimization problems in a Hilbert space. Our goal is to obtain an ε-approximate solution of the problem in the presence of computational errors, where ε is a given positive number. We show that the extragradient method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.

Keywords: Extragradient Method; Constrained Convex Minimization Problem; Computational Errors; Good Approximate Solution; Hilbert Space (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-30921-7_7

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DOI: 10.1007/978-3-319-30921-7_7

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