Noise-enhanced convolutional neural networks

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation–maximization (EM) algorithm and be...

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Vydáno v:	Neural networks Ročník 78; s. 15 - 23
Hlavní autoři:	Audhkhasi, Kartik, Osoba, Osonde, Kosko, Bart
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Ltd 01.06.2016
Témata:	Algorithms Back propagation Backpropagation Convolutional neural network Expectation–maximization algorithm Hyperplanes Learning - physiology Likelihood Functions Neural networks Neural Networks (Computer) Noise Noise injection Normal Distribution Random Allocation Sampling from big data sets Stochastic resonance Training Backpropagation Noise injection Sampling from big data sets Stochastic resonance Expectation–maximization algorithm Convolutional neural network
ISSN:	0893-6080, 1879-2782, 1879-2782
On-line přístup:	Získat plný text
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