Results 21 to 30 of about 252 (217)
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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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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Entropy, 2023 In this paper, we present a general framework that provides a comprehensive and uniform treatment of integral majorization inequalities for convex functions and finite signed measures.
László Horváth
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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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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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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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Variational f-divergence Minimization
CoRR, 2019 Probabilistic models are often trained by maximum likelihood, which corresponds to minimizing a specific f-divergence between the model and data distribution. In light of recent successes in training Generative Adversarial Networks, alternative non-likelihood training criteria have been proposed.
Mingtian Zhang +4 more
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Fragmentation functions for gluon into B c or B c ∗ $$ {B}_c^{\ast } $$ meson
Journal of High Energy Physics, 2022 In the paper, we calculate the fragmentation functions for g → B c and g → B c ∗ $$ {B}_c^{\ast } $$ . The ultraviolet divergences in the calculation are removed through the renormalization of the operator definition of the fragmentation functions under ...
Xu-Chang Zheng +2 more
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Refinement of the Jensen integral inequality
Open Mathematics, 2016 In this paper we give a refinement of Jensen’s integral inequality and its generalization for linear functionals. We also present some applications in Information Theory.
Sever Dragomir Silvestru +2 more
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