Normalized convergence in stochastic optimization
Authors: Ermoliev Y, Norkin VI
Publication Year: 1991
Reference: Annals of Operations Research, 30(1):187-198 [1991]
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.
KEYWORDS: Probability theory; normalized convergence; stochastic optimization; statistical approach; rate of convergence
KEYWORDS: Probability theory; normalized convergence; stochastic optimization; statistical approach; rate of convergence
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