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The AIC Criterion and Symmetrizing the Kullback–Leibler Divergence
IEEE Transactions on Neural Networks, 2007 Abd‐Krim Seghouane +1 more
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Entropy, 2022 By calculating the Kullback–Leibler divergence between two probability measures belonging to different exponential families dominated by the same measure, we obtain a formula that generalizes the ordinary Fenchel–Young divergence.
Frank Nielsen
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Kullback-Leibler divergence for detection of rare haplotype common disease association. [PDF]
Eur J Hum Genet, 2015 Lin S.
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The Kullback-Leibler Divergence Class in Decoding the Chest Sound Pattern [PDF]
Informatică economică, 2019 Kullback-Leibler Divergence Class or relative entropy is a special case of broader divergence. It represents a calculation of how one probability distribution diverges from another one, expected probability distribution. Kullback-Leibler divergence has a
Antonio CLIM, Razvan Daniel ZOTA
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Chained Kullback-Leibler divergences [PDF]
2016 IEEE International Symposium on Information Theory (ISIT), 2016 We define and characterize the "chained" Kullback-Leibler divergence min w D(p‖w) + D(w‖q) minimized over all intermediate distributions w and the analogous k-fold chained K-L divergence min D(p‖wk-1) + … + D(w2‖w1) + D(w1‖q) minimized over the entire path (w1,…,wk-1).
Dmitri S, Pavlichin, Tsachy, Weissman
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ESTIMATION OF THE KULLBACK-LEIBLER DIVERGENCE
, 2003 The Kullback-Leibler (KL) divergence K(fl, P) between a set O of probability measures (PMs) on ]R d and some PM P cannot be estimated by K(O, Pn) when O contains PM whose support is not included in the support of the empirical measure Pn. We propose an estimation procedure which avoids any smoothing of Pn.
Michel Broniatowski
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Model Averaging Estimation Method by Kullback–Leibler Divergence for Multiplicative Error Model
Complexity, 2022 In this paper, we propose the model averaging estimation method for multiplicative error model and construct the corresponding weight choosing criterion based on the Kullback–Leibler divergence with a hyperparameter to avoid the problem of overfitting ...
Wanbo Lu, Wenhui Shi
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On Voronoi Diagrams on the Information-Geometric Cauchy Manifolds
Entropy, 2020 We study the Voronoi diagrams of a finite set of Cauchy distributions and their dual complexes from the viewpoint of information geometry by considering the Fisher-Rao distance, the Kullback-Leibler divergence, the chi square divergence, and a flat ...
Frank Nielsen
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Kullback-Leibler Divergence and Mutual Information of Experiments in the Fuzzy Case
Axioms, 2017 The main aim of this contribution is to define the notions of Kullback-Leibler divergence and conditional mutual information in fuzzy probability spaces and to derive the basic properties of the suggested measures.
Dagmar Markechová
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Kullback–Leibler Divergence and Mutual Information of Partitions in Product MV Algebras
Entropy, 2017 The purpose of the paper is to introduce, using the known results concerning the entropy in product MV algebras, the concepts of mutual information and Kullback–Leibler divergence for the case of product MV algebras and examine algebraic properties of ...
Dagmar Markechová, Beloslav Riečan
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