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• W2172028470 abstract "We explore the relationship between weighted averaging and stochastic approximation algorithms, and study their convergence via a sample-path analysis. We prove that the convergence of a stochastic approximation algorithm is equivalent to the convergence of the weighted average of the associated noise sequence. We also present necessary and sufficient noise conditions for convergence of the average of the output of a stochastic approximation algorithm in the linear case. We show that the averaged stochastic approximation algorithms can tolerate a larger class of noise sequences than the stand-alone stochastic approximation algorithms." @default.
• W2172028470 created "2016-06-24" @default.
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• W2172028470 date "2002-12-24" @default.
• W2172028470 modified "2023-10-16" @default.
• W2172028470 title "Weighted averaging and stochastic approximation" @default.
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• W2172028470 doi "https://doi.org/10.1109/cdc.1996.574643" @default.
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