Results 31 to 40 of about 204,288 (176)
Manipulating Voice Attributes by Adversarial Learning of Structured Disentangled Representations
Entropy, 2023 Voice conversion (VC) consists of digitally altering the voice of an individual to manipulate part of its content, primarily its identity, while maintaining the rest unchanged.
Laurent Benaroya +2 more
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Kullback–Leibler Divergence Measure for Multivariate Skew-Normal Distributions
Entropy, 2012 The aim of this work is to provide the tools to compute the well-known Kullback–Leibler divergence measure for the flexible family of multivariate skew-normal distributions.
Reinaldo B. Arellano-Valle +1 more
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Entropy, 2022 The study of leukemia classification using deep learning techniques has been conducted by multiple research teams worldwide. Although deep convolutional neural networks achieved high quality of sick vs. healthy patient discrimination, their inherent lack
Krzysztof Pałczyński +2 more
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Principle of Minimum Discrimination Information and Replica Dynamics
Entropy, 2010 Dynamics of many complex systems can be described by replicator equations (RE). Here we present an effective method for solving a wide class of RE based on reduction theorems for models of inhomogeneous communities.
Georgiy P. Karev
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Journal of Imaging, 2022 Dimensionality reduction techniques are often used by researchers in order to make high dimensional data easier to interpret visually, as data visualization is only possible in low dimensional spaces. Recent research in nonlinear dimensionality reduction
Liliya A. Demidova, Artyom V. Gorchakov
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Sum-α Stopping Criterion for Turbo Decoding [PDF]
International Journal of Electronics and Telecommunications, 2021 In this article, we propose a new stopping criterion for turbo codes. This criterion is based on the behaviour of the probabilistic values alpha 'α' calculated in the forward recursion during turbo decoding. We called this criterion Sum-α. The simulation
Aissa Ouardi
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Spoofing Cross-Entropy Measure in Boson Sampling
Physical Review Letters, 2023 7+11 pages, 5+6 ...
Changhun Oh, Liang Jiang, Bill Fefferman
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HEAVY TAILS, IMPORTANCE SAMPLING AND CROSS–ENTROPY [PDF]
Stochastic Models, 2005 ABSTRACT We consider the problem of estimating ℙ(Y 1 + … + Y n > x) by importance sampling when the Y i are i.i.d. and heavy-tailed. The idea is to exploit the cross-entropy method as a tool for choosing good parameters in the importance sampling distribution; in doing sso, we use the asymptotic description that given ℙ(Y 1 + … + Y n > x), n − 1 of ...
Asmussen, S. +2 more
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Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting
, 2017 We propose a max-pooling based loss function for training Long Short-Term Memory (LSTM) networks for small-footprint keyword spotting (KWS), with low CPU, memory, and latency requirements.
Fu, Gengshen +8 more
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The cross-entropy method for continuous multi-extremal optimization [PDF]
, 2006 In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization.
A. Webb +23 more
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