Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent

Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent

In this paper we propose the fractional gradient descent for increasing the training and work of modern neural networks. This optimizer searches the global minimum of the loss function considering the fractional gradient directions achieved by Riemann-Liouville, Caputo, and Grunwald-Letnikov derivat...

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Bibliografische gegevens
Hoofdauteurs:	Abdulkadirov, R. I., Абдулкадиров, Р. И., Lyakhov, P. A., Ляхов, П. А., Baboshina, V. A., Бабошина, В. А., Nagornov, N. N., Нагорнов, Н. Н.
Formaat:	Статья
Taal:	English
Gepubliceerd in:	Institute of Electrical and Electronics Engineers Inc. 2024
Onderwerpen:	Caputo Stochastic gradient descent Convolutional neural networks Fractional derivatives of Riemann-Liouville Grunwald-Letnikov Multilayer perceptron Optimization algorithms
Online toegang:	https://dspace.ncfu.ru/handle/123456789/29336
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!

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