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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書誌詳細
主要な著者:	Abdulkadirov, R. I., Абдулкадиров, Р. И., Lyakhov, P. A., Ляхов, П. А., Baboshina, V. A., Бабошина, В. А., Nagornov, N. N., Нагорнов, Н. Н.
フォーマット:	Статья
言語:	English
出版事項:	Institute of Electrical and Electronics Engineers Inc. 2024
主題:	Caputo Stochastic gradient descent Convolutional neural networks Fractional derivatives of Riemann-Liouville Grunwald-Letnikov Multilayer perceptron Optimization algorithms
オンライン･アクセス:	https://dspace.ncfu.ru/handle/123456789/29336
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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