Results 21 to 30 of about 7,533,665 (302)
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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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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Generalized Csiszár's f-divergence for Lipschitzian functions [PDF]
Mathematical Inequalities & Applications, 2021 We started with the generalization of the Csisz ́ar’s f -divergence. We stated and proved Jensen’s type inequality for L-Lipschitzian functions. The results for commonly used examples of f-divergences, such as the Kullbach-Leibler divergence, the Hellinger divergence, the R ́enyi divergence and χ2 -distance are derived.
Pečarić D., Pečarić J., Pokaz D.
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Monotonic multi-state quantum $f$-divergences
, 2022 We use the Tomita-Takesaki modular theory and the Kubo-Ando operator mean to write down a large class of multi-state quantum $f$-divergences and prove that they satisfy the data processing inequality.
Ouseph, Shoy +2 more
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Blind Deconvolution of Seismic Data Using f-Divergences
Entropy, 2011 This paper proposes a new approach to the seismic blind deconvolution problem in the case of band-limited seismic data characterized by low dominant frequency and short data records, based on Csiszár’s f-divergence.
Bing Zhang, Jing-Huai Gao
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QUANTUM f-DIVERGENCES AND ERROR CORRECTION [PDF]
Reviews in Mathematical Physics, 2011 Quantum f-divergences are a quantum generalization of the classical notion of f-divergences, and are a special case of Petz' quasi-entropies. Many well-known distinguishability measures of quantum states are given by, or derived from, f-divergences. Special examples include the quantum relative entropy, the Rényi relative entropies, and the Chernoff ...
Hiai, F. +3 more
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On f-divergences Between Cauchy Distributions [PDF]
IEEE Transactions on Information Theory, 2021 We prove that the $f$-divergences between univariate Cauchy distributions are all symmetric, and can be expressed as strictly increasing scalar functions of the symmetric chi-squared divergence. We report the corresponding scalar functions for the total variation distance, the Kullback-Leibler divergence, the squared Hellinger divergence, and the ...
Frank Nielsen, Kazuki Okamura
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NLO fragmentation functions for a quark into a spin-singlet quarkonium: same flavor case
Journal of High Energy Physics, 2021 In the paper, we calculate the fragmentation functions for c → η c and b → η b up to next-to-leading-order (NLO) QCD accuracy. The ultraviolet divergences in the real corrections are removed through operator renormalization under the modified min- imal ...
Xu-Chang Zheng +2 more
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