Results 11 to 20 of about 252 (217)
Reviews in Mathematical Physics, 2023 The main result in this paper shows that the quantum [Formula: see text]-divergence of two states is equal to the classical [Formula: see text]-divergence of the corresponding Nussbaum–Szkoła distributions. This provides a general framework for studying certain properties of quantum entropic quantities using the corresponding classical entities.
Androulakis, George, John, Tiju Cherian
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Imitation Learning as f-Divergence Minimization [PDF]
, 2021 International Workshop on the Algorithmic Foundations of Robotics (WAFR ...
Liyiming Ke +5 more
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Inequalities for Jensen–Sharma–Mittal and Jeffreys–Sharma–Mittal Type f–Divergences
Entropy, 2021 In this paper, we introduce new divergences called Jensen–Sharma–Mittal and Jeffreys–Sharma–Mittal in relation to convex functions. Some theorems, which give the lower and upper bounds for two new introduced divergences, are provided.
Paweł A. Kluza
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Distances Based on the Perimeter of the Risk Set of a Testing Problem
Austrian Journal of Statistics, 2016 At the core of this paper is a simple geometric object, namely the risk set of a statistical testing problem on the one hand and f-divergences, which were introduced by Csiszár (1963) on the other hand.
Ferdinand Österreicher
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On a Generalization of the Jensen–Shannon Divergence and the Jensen–Shannon Centroid
Entropy, 2020 The Jensen−Shannon divergence is a renown bounded symmetrization of the Kullback−Leibler divergence which does not require probability densities to have matching supports. In this paper, we introduce a vector-skew generalization of the scalar
Frank Nielsen
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On Pairs of $f$-Divergences and Their Joint Range [PDF]
IEEE Transactions on Information Theory, 2011 7 pages, 4 ...
Peter Harremoës, Igor Vajda
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f-Divergence Variational Inference
CoRR, 2020 This paper introduces the $f$-divergence variational inference ($f$-VI) that generalizes variational inference to all $f$-divergences. Initiated from minimizing a crafty surrogate $f$-divergence that shares the statistical consistency with the $f$-divergence, the $f$-VI framework not only unifies a number of existing VI methods, e.g.
Neng Wan, Dapeng Li, Naira Hovakimyan
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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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On Relations Between the Relative Entropy and χ2-Divergence, Generalizations and Applications
Entropy, 2020 The relative entropy and the chi-squared divergence are fundamental divergence measures in information theory and statistics. This paper is focused on a study of integral relations between the two divergences, the implications of these relations, their ...
Tomohiro Nishiyama, Igal Sason
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Optimized Quantum F-Divergences [PDF]
2018 IEEE International Symposium on Information Theory (ISIT), 2018 5 pages; shortened, more accessible version of arXiv:1710.10252; making publicly available due to public access mandate of US National Science Foundation and flag on Google ...
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