Fast Approximations of the Jeffreys Divergence between Univariate Gaussian Mixtures via Mixture Conversions to Exponential-Polynomial Distributions

The Jeffreys divergence is a renown arithmetic symmetrization of the oriented Kullback–Leibler divergence broadly used in information sciences. Since the Jeffreys divergence between Gaussian mixture models is not available in closed-form, various techniques with advantages and disadvantages have bee...

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Auteur principal: Frank Nielsen
Format: article
Langue:EN
Publié: MDPI AG 2021
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Accès en ligne:https://doaj.org/article/f8ed504ac684481fb7f860145ec5bc48
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