Upper Bounds on the Expected Value of a Convex Function Using Gradient and Conjugate Function Information.

Abstract

New upper bounds are given for the expected value of a convex function. The bounds employ subgradient information and the conjugate function. The bounds are derived and compared with previous bounds with different information requirements. Keywords: Bounds; Convex functions; Stochastic programs; Utility functions.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1987
Accession Number
ADA186246

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  • John R. Birge
  • Marck Teboulle

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  • University of Michigan

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