Results 41 to 50 of about 255,284 (162)
On the Jensen–Shannon Symmetrization of Distances Relying on Abstract Means
Entropy, 2019 The Jensen–Shannon divergence is a renowned bounded symmetrization of the unbounded Kullback–Leibler divergence which measures the total Kullback–Leibler divergence to the average mixture distribution.
Frank Nielsen
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Algorithms for Nonnegative Matrix Factorization with the Kullback–Leibler Divergence [PDF]
Journal of Scientific Computing, 2021 Nonnegative matrix factorization (NMF) is a standard linear dimensionality reduction technique for nonnegative data sets. In order to measure the discrepancy between the input data and the low-rank approximation, the Kullback-Leibler (KL) divergence is one of the most widely used objective function for NMF.
Le, Thi Khanh Hien, Gillis, Nicolas
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Rényi Divergence and Kullback-Leibler Divergence
, 2013 Accepted by IEEE Transactions on Information Theory. To appear.Rényi divergence is related to Rényi entropy much like Kullback-Leibler divergence is related to Shannon's entropy, and comes up in many settings.
Harremoës, Peter, van Erven, Tim
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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 +6 more
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Zipf–Mandelbrot law, f-divergences and the Jensen-type interpolating inequalities
Journal of Inequalities and Applications, 2018 Motivated by the method of interpolating inequalities that makes use of the improved Jensen-type inequalities, in this paper we integrate this approach with the well known Zipf–Mandelbrot law applied to various types of f-divergences and distances, such ...
Neda Lovričević +2 more
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Android Malware Detection Using Kullback-Leibler Divergence
Advances in Distributed Computing and Artificial Intelligence Journal, 2015 Many recent reports suggest that mareware applications cause high billing to victims by sending and receiving hidden SMS messages. Given that, there is a need to develop necessary technique to identify malicious SMS operations as well as differentiate ...
Vanessa N. COOPER +2 more
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Some Inequalities For The Kullback-Leibler And x²−Distances In Information Theory And Applications [PDF]
, 2000 Inequalities for the Kullback-Leibler and x²−distances and applications for Shannon’s entropy and mutual information are ...
Dragomir, Sever S, Gluscevic, Vido
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Divergence Measure of Belief Function and Its Application in Data Fusion
IEEE Access, 2019 Divergence measure is widely used in many applications. To efficiently deal with uncertainty in real applications, basic probability assignment (BPA) in Dempster-Shafer evidence theory, instead of probability distribution, is adopted.
Yutong Song, Yong Deng
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Technical Notes on Kullback-Leibler Divergence
, 2019 I provide some technical notes regarding the Kullback-Leibler divergence. Derivations of the Kullback-Leibler divergence are provided for Bernoulli, Geometric, Poisson, Exponential, and Normal ...
Alexander Etz
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Enhancing timbre model using MFCC and its time derivatives for music similarity estimation
, 2012 One of the popular methods for content-based music similarity estimation is to model timbre with MFCC as a single multivariate Gaussian with full covariance matrix, then use symmetric Kullback-Leibler divergence.
Martinez, Kirk, de leon, Franz
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