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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/306199
Title: Neural network software technology trainable on the random search and gradient descent principles
Authors: Matskevich, Vadim V.
Zhou, Xi
Bu, Qing
Keywords: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика
ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
Issue Date: 2023
Publisher: Minsk : BSU
Citation: Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 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://elib.bsu.by/handle/123456789/306199
ISBN: 978-985-881-522-6
Licence: info:eu-repo/semantics/openAccess
Appears in Collections:2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons

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