Normalized convergence in stochastic optimization

Normalized convergence in stochastic optimization

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Article ID: iaor19912122
Country: Switzerland
Volume: 30
Start Page Number: 187
End Page Number: 198
Publication Date: Mar 1991
Journal: Annals of Operations Research
Authors: ,
Abstract:

A new concept of (normalized) convergence of random variables is introduced. This convergence is preserved under Lipschitz transformations, follows from convergence in mean and itself implies convergence in probability. If a sequence of random variables satisfies a limit theorem then it is a normalized convergent sequence. The introduced concept is applied to the convergence rate study of a statistical approach in stochastic optimization.

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