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Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding
Neural Information Processing Systems, 2020Variational Autoencoders (VAEs) have seen widespread use in learned image compression. They are used to learn expressive latent representations on which downstream compression methods can operate with high efficiency.
Gergely Flamich +2 more
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Relative Entropy and Relative Entropy of Entanglement for Infinite-Dimensional Systems
International Journal of Theoretical Physics, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhoubo Duan +3 more
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Signomial and polynomial optimization via relative entropy and partial dualization
Mathematical Programming Computation, 2019We describe a generalization of the Sums-of-AM/GM-Exponential (SAGE) methodology for relative entropy relaxations of constrained signomial and polynomial optimization problems.
Riley Murray +2 more
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Relative entropy for coherent states in chiral CFT
Letters in Mathematical Physics, 2019We consider the relative entropy between the vacuum state and a state obtained by applying an exponentiated stress tensor to the vacuum of a chiral conformal field theory on the lightray.
S. Hollands
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Causation and information flow with respect to relative entropy.
Chaos, 2018Recently, a rigorous formalism has been established for information flow and causality within dynamical systems with respect to Shannon entropy. In this study, we re-establish the formalism with respect to relative entropy, or Kullback-Leiber divergence,
X. Liang
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Newton Polytopes and Relative Entropy Optimization
Foundations of Computational Mathematics, 2018Certifying function nonnegativity is a ubiquitous problem in computational mathematics, with especially notable applications in optimization. We study the question of certifying nonnegativity of signomials based on the recently proposed approach of Sums ...
Riley Murray +2 more
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Multichannel relative-entropy spectrum analysis
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1986A new relative-entropy method is presented for estimating the power spectral density matrix for multichannel data, given correlation values for linear combinations of the channels, and given an initial estimate of the spectral density matrix. A derivation of the method from the relative-entropy-principle is given.
R. Johnson, B. Musicus
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Mismatched Estimation and Relative Entropy
IEEE Transactions on Information Theory, 2009A random variable with distribution P is observed in Gaussian noise and is estimated by a mismatched minimum mean-square estimator that assumes that the distribution is Q, instead of P . This paper shows that the integral over all signal-to-noise ratios (SNRs) of the excess mean-square estimation error incurred by the mismatched estimator is twice the ...
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Relative entropy and learning rules
Physical Review A, 1991The dynamics of a probabilistic neural network is characterized by the distribution \ensuremath{\nu}(x'\ensuremath{\Vert}x) of successor states x' of an arbitrary state x of the network. A prescribed memory or behavior pattern is represented in terms of an ordered sequence of network states ${\mathit{x}}^{(1)}$,${\mathit{x}}^{(2)}$,...,${\mathit{x}}^{(\
, Qian, , Gong, , Clark
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SMKFC-ER: Semi-supervised multiple kernel fuzzy clustering based on entropy and relative entropy
Information Sciences, 2021Fariba Salehi, M. Keyvanpour, A. Sharifi
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