Results 11 to 20 of about 59,513 (222)
Bounds for Kullback-Leibler divergence [PDF]
Electronic Journal of Differential Equations, 2016 Entropy, conditional entropy and mutual information for discrete-valued random variables play important roles in the information theory. The purpose of this paper is to present new bounds for relative entropy $D(p||q)$ of two probability distributions
Pantelimon G. Popescu +3 more
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Statistical Estimation of the Kullback–Leibler Divergence [PDF]
Mathematics, 2021 Asymptotic unbiasedness and L2-consistency are established, under mild conditions, for the estimates of the Kullback–Leibler divergence between two probability measures in Rd, absolutely continuous with respect to (w.r.t.) the Lebesgue measure.
Alexander Bulinski, Denis Dimitrov
doaj +3 more sources
R\'enyi Divergence and Kullback-Leibler Divergence [PDF]
IEEE Transactions on Information Theory, 2013 R\'enyi divergence is related to R\'enyi entropy much like Kullback-Leibler divergence is related to Shannon's entropy, and comes up in many settings.
Harremoës, Peter, van Erven, Tim
core +3 more sources
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 Riecan
exaly +3 more sources
Kullback Leibler divergence in complete bacterial and phage genomes [PDF]
PeerJ, 2017 The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism.
Sajia Akhter +5 more
doaj +3 more sources
Local inconsistency detection using the Kullback–Leibler divergence measure [PDF]
Systematic ReviewsBackground The standard approach to local inconsistency assessment typically relies on testing the conflict between the direct and indirect evidence in selected treatment comparisons.
Loukia M. Spineli
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Kullback–Leibler Divergence Measure for Multivariate Skew-Normal Distributions
Entropy, 2012 The aim of this work is to provide the tools to compute the well-known Kullback–Leibler divergence measure for the flexible family of multivariate skew-normal distributions.
Javier E Contreras-Reyes +1 more
exaly +3 more sources
Some Order Preserving Inequalities for Cross Entropy and Kullback–Leibler Divergence [PDF]
Entropy, 2018 Cross entropy and Kullback⁻Leibler (K-L) divergence are fundamental quantities of information theory, and they are widely used in many fields. Since cross entropy is the negated logarithm of likelihood, minimizing cross entropy is equivalent to ...
Mateu Sbert +3 more
doaj +2 more sources
Fault-tolerant relative navigation based on Kullback–Leibler divergence
International Journal of Advanced Robotic Systems, 2020 A fault-detection method for relative navigation based on Kullback–Leibler divergence (KLD) is proposed. Different from the traditional χ 2 -based approaches, the KLD for a filter is following a hybrid distribution that combines χ 2 distribution and F ...
Jun Xiong +2 more
exaly +2 more sources
On the Interventional Kullback-Leibler Divergence
CoRR, 2023 Modern machine learning approaches excel in static settings where a large amount of i.i.d. training data are available for a given task. In a dynamic environment, though, an intelligent agent needs to be able to transfer knowledge and re-use learned components across domains. It has been argued that this may be possible through causal models, aiming to
Jonas Bernhard Wildberger +3 more
openaire +5 more sources