Normalized Convergence in Stochastic Optimization

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/3294 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/3294 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/3294 archive 351 disk0/00/00/32/53 2016-01-15 01:59:32 2021-08-27 17:13:32 2016-01-15 01:59:32 monograph show 3 Ermoliev Y.M. 1445 Norkin V.I. AL1055 Normalized Convergence in Stochastic Optimization pub iis_met prog_ado A new concept of (normalized) convergence of random variables is introduced. The normalized convergence in preserved under Lipschitz transformations. This convergence follows from the convergence in mean and itself implies the convergence in probability. If a sequence of random variables satisfies a Limit theorem then it in a normalized convergent sequence. The introduced concept is applied to the convergence rate study of a statistical approach in stochastic optimization. 1989-11 published WP-89-091 WP-89-091 10 338 2245 public working_paper IIASA, Laxenburg, Austria 23 FALSE info:eu-repo/semantics/book