A Projected Subgradient Method for Nonsmooth Problems

Alexander Zaslavski
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Alexander Zaslavski: Israel Institute of Technology

Chapter Chapter 12 in Convex Optimization with Computational Errors, 2020, pp 321-354 from Springer

Abstract: Abstract In this chapter we study the convergence of the projected subgradient method for a class of constrained optimization problems in a Hilbert space. For this class of problems, an objective function is assumed to be convex but a set of admissible points is not necessarily convex. Our goal is to obtain an 𝜖-approximate solution in the presence of computational errors, where 𝜖 is a given positive number.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-37822-6_12

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DOI: 10.1007/978-3-030-37822-6_12

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