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.
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References
Zaslavski AJ (2010) The projected subgradient method for nonsmooth convex optimization in the presence of computational errors. Numer Funct Anal Optim 31:616–633
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© 2016 Springer International Publishing Switzerland
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Zaslavski, A.J. (2016). A Projected Subgradient Method for Nonsmooth Problems. In: Numerical Optimization with Computational Errors. Springer Optimization and Its Applications, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-319-30921-7_8
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DOI: https://doi.org/10.1007/978-3-319-30921-7_8
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30920-0
Online ISBN: 978-3-319-30921-7
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