Stochastic Optimization Techniques for Finding Optimal Submeasures

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/2727 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/2727 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/2727 archive 351 disk0/00/00/26/72 2016-01-15 01:56:04 2021-08-27 17:12:24 2016-01-15 01:56:04 monograph show 3 Gaivoronski A.A. 1003 Stochastic Optimization Techniques for Finding Optimal Submeasures pub iis_met prog_ado 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. 1985-05 published WP-85-028 WP-85-028 1273 public working_paper IIASA, Laxenburg, Austria 57 FALSE info:eu-repo/semantics/book