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A probabilistic interpretation of the constant gain algorithm

Berardi, Michele (2019): A probabilistic interpretation of the constant gain algorithm.

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Abstract

This paper proposes a novel interpretation of the constant gain learning algorithm through a probabilistic setting with Bayesian updating. Such framework allows to understand the gain coefficient in terms of the probability of changes in the estimated quantity.

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