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A method of aggregate stochastic subgradients with on-line stepsize rules for convex stochastic programming problems

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Stochastic Programming 84 Part II

Part of the book series: Mathematical Programming Studies ((MATHPROGRAMM,volume 28))

Abstract

A new stochastic subgradient algorithm for solving convex stochastic programming problems is described. It uses an auxiliary filter to average stochastic subgradients observed and is provided with on-line rules for determining stepsizes and filter gains in the course of computation. Convergence with probability one is proved and numerical examples are described.

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Andras Prékopa Roger J.- B. Wets

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© 1986 The Mathematical Programming Society, Inc.

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Ruszczyński, A., Syski, W. (1986). A method of aggregate stochastic subgradients with on-line stepsize rules for convex stochastic programming problems. In: Prékopa, A., Wets, R.J.B. (eds) Stochastic Programming 84 Part II. Mathematical Programming Studies, vol 28. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0121128

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  • DOI: https://doi.org/10.1007/BFb0121128

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00926-6

  • Online ISBN: 978-3-642-00927-3

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