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The cross entropy method for classification
Proceedings of the 22nd international conference on Machine learning - ICML '05, 2005We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term instead of the L1 or L2 norms. In order to solve the optimization problem we use the cross entropy method to search over the possible sets of support vectors.
Shie Mannor +2 more
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An Efficient Method for Computation of Entropy and Joint Entropy of Images
2020This paper proposes an efficient method to compute entropy and joint entropy of images. Entropy of images is used to determine its quality. It is defined as the randomness or uncertainty present in the image. Similarly, joint entropy is a measure of the uncertainty present in the overlapped region of two images.
Debapriya Sengupta +2 more
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Entropy methods in hydrodynamic scaling
1992We shall describe these methods by examining very closely an explicit model. Consider N lattice sites arranged periodically in one dimension with a lattice spacing of 1/N. We have spin variables x j attached to each site j/N, the sites being viewed as equally spaced points on the circle of unit circumference. The spins x j vary in time in such a manner
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Extension to the maximum entropy method
IEEE Transactions on Information Theory, 1977The maximum entropy method provides an estimate of the power spectral density which maximizes the entropy of a stationary random process from the first N lags of the autocorrelation function. The method is applied to cases where some of the first N autocorrelation function lags are unknown.
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Nuclear Instruments and Methods in Physics Research, 1984
For some years now two different entropy expressions have been in use for maximum entropy image restoration and there has been some controversy over which one is appropriate for a given problem. Here two further entropies are presented and it is argued that there is no single correct algorithm.
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For some years now two different entropy expressions have been in use for maximum entropy image restoration and there has been some controversy over which one is appropriate for a given problem. Here two further entropies are presented and it is argued that there is no single correct algorithm.
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A Dual Method for Maximum Entropy Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979A simple iterative dual algorithm for maximum entropy image restoration is presented. The dual algorithm involves fewer parameters than conventional minimization in the image space. Mini-computer test results for Fourier synthesis with inadequate phantom data are given.
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2009
The cross-entropy (CE) method [56] is a general Monte Carlo approach to combinatorial and continuous multi-extremal optimization [195]. The method originated from the field of rare event simulation, where very small probabilities need to be accurately estimated.
Wesam Ashour Barbakh +2 more
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The cross-entropy (CE) method [56] is a general Monte Carlo approach to combinatorial and continuous multi-extremal optimization [195]. The method originated from the field of rare event simulation, where very small probabilities need to be accurately estimated.
Wesam Ashour Barbakh +2 more
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2022
The maximum entropy method, originating from Jaynes’ maximum entropy principle, has been a numerical scheme that recovers a density function when its several moments are known. From Shannon’s entropy for discrete sample spaces to Boltzmann’s entropy for density functions and to the invention of the spline maximum entropy method, we survey some of
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The maximum entropy method, originating from Jaynes’ maximum entropy principle, has been a numerical scheme that recovers a density function when its several moments are known. From Shannon’s entropy for discrete sample spaces to Boltzmann’s entropy for density functions and to the invention of the spline maximum entropy method, we survey some of
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1999
In Chapter 1 we introduced in the context of interacting particle systems the physical concepts of local equilibrium and conservation of local equilibrium and we proved the persistence of local equilibrium in a model where particles evolve independently.
Claude Kipnis, Claudio Landim
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In Chapter 1 we introduced in the context of interacting particle systems the physical concepts of local equilibrium and conservation of local equilibrium and we proved the persistence of local equilibrium in a model where particles evolve independently.
Claude Kipnis, Claudio Landim
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2013
The main subject of this thesis is to extract the spectral function of a specific interpolating field from the OPE of its correlator. For this task, we propose to use the maximum entropy method (MEM), which allows us the obtain the spectral function without any assumptions on its functional form.
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The main subject of this thesis is to extract the spectral function of a specific interpolating field from the OPE of its correlator. For this task, we propose to use the maximum entropy method (MEM), which allows us the obtain the spectral function without any assumptions on its functional form.
openaire +1 more source