Geodesic
A note on how Rényi entropy can create a spectrum of probabilistic merging operators
Kybernetika, Tome 55 (2019) no. 4, pp. 605-617.

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In this paper we present a result that relates merging of closed convex sets of discrete probability functions respectively by the squared Euclidean distance and the Kullback-Leibler divergence, using an inspiration from the Rényi entropy. While selecting the probability function with the highest Shannon entropy appears to be a convincingly justified way of representing a closed convex set of probability functions, the discussion on how to represent several closed convex sets of probability functions is still ongoing. The presented result provides a perspective on this discussion. Furthermore, for those who prefer the standard minimisation based on the squared Euclidean distance, it provides a connection to a probabilistic merging operator based on the Kullback-Leibler divergence, which is closely connected to the Shannon entropy.
DOI : 10.14736/kyb-2019-4-0605
Classification : 52A99, 52C99
Keywords: probabilistic merging; information geometry; Kullback–Leibler divergence; Rényi entropy 
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Adamčík, Martin. A note on how Rényi entropy can create a spectrum of probabilistic merging operators. Kybernetika, Tome 55 (2019) no. 4, pp. 605-617. doi : 10.14736/kyb-2019-4-0605. http://geodesic.mathdoc.fr/articles/10.14736/kyb-2019-4-0605/

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