https://libeldoc.bsuir.by/handle/123456789/54297
Title: | Neural network software technology trainable on the random search and gradient descent principles |
Authors: | Matskevich, V. A. Xi Zhou Qing Bu |
Keywords: | материалы конференций;framework;neural network;training algorithms;random search algorithms;annealing method |
Issue Date: | 2023 |
Publisher: | BSU |
Citation: | Matskevich, V. A. Neural network software technology trainable on the random search and gradient descent principles / V. A. Matskevich, Xi Zhou, Qing Bu // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 64–67. |
Abstract: | The paper considers an applied problem related to the construction of efficient neural network technologies implemented in the traditional frameworks' standards. It is shown that the increase in efficiency is achieved due to the additional inclusion in the framework's structure of training algorithms based on the ideas of random search. Original implementations of such algorithms are proposed, with experimental confirmation of their effectiveness. It is shown that in this case not only the solutions' obtained quality increases, but it is also possible to extend the range of applied problems to be solved. |
URI: | https://libeldoc.bsuir.by/handle/123456789/54297 |
Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) |
File | Description | Size | Format | |
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Matskevich_Neural.pdf | 243.1 kB | Adobe PDF | View/Open |
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