Stochastic optimization techniques for finding optimal submeasures

Gaivoronski, A. (1986). Stochastic optimization techniques for finding optimal submeasures. In: Stochastic Optimization. Eds. Arkin, V.i., Shiraev, I., & Wets, R., pp. 351-363 Germany: Springer Berlin Heidelberg. ISBN 978-3-540-39841-7 10.1007/BFb0007112.

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Abstract

In this paper, the author looks at some quite general optimization problems on the space of probabilistic measures. These problems originated in mathematical statistics but have applications in several other areas of mathematical analysis. The author extends previous work by considering a more general form of the constraints, and develops numerical methods (based on stochastic quasigradient techniques) and some duality relations for problems of this type. This paper is a contribution to research on stochastic optimization currently underway within the Adaptation and Optimization Project.

Item Type:	Book Section
Depositing User:	Romeo Molina
Date Deposited:	12 Dec 2016 15:47
Last Modified:	27 Aug 2021 17:28
URI:	https://pure.iiasa.ac.at/14129

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