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Sampling and Optimizing

  • J. Frédéric BonnansEmail author
Chapter
Part of the Universitext book series (UTX)

Abstract

This chapter discusses what happens when, instead of minimizing an expectation, one minimizes the sample approximation obtained by getting a sample of independent events. The analysis relies on the theory of asymptotic laws (delta theorems) and its applications in stochastic programming. We extend the results to the case of constraints in expectation.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Inria-Saclay and Centre de Mathématiques AppliquéesÉcole PolytechniquePalaiseauFrance

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