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Titlebook: Proceedings of ELM 2021; Theory, Algorithms a Kaj-Mikael Björk Conference proceedings 2023 The Editor(s) (if applicable) and The Author(s),

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书目名称Proceedings of ELM 2021
副标题Theory, Algorithms a
编辑Kaj-Mikael Björk
视频video
概述Provides recent research on Extreme Learning Machines (ELM).Contains selected papers from the 11th International Conference on Extreme Learning Machines 2022.Presents theory, algorithms, and applicati
丛书名称Proceedings in Adaptation, Learning and Optimization
图书封面Titlebook: Proceedings of ELM 2021; Theory, Algorithms a Kaj-Mikael Björk Conference proceedings 2023 The Editor(s) (if applicable) and The Author(s),
描述.This book contains papers from the International Conference on Extreme Learning Machine 2021, which was held in virtual on December 15–16, 2021. Extreme learning machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training dataand application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neuron
出版日期Conference proceedings 2023
关键词Intelligent Systems; Extreme Learning Machine; ELM 2021; The International Conference on Extreme Learni
版次1
doihttps://doi.org/10.1007/978-3-031-21678-7
isbn_softcover978-3-031-21680-0
isbn_ebook978-3-031-21678-7Series ISSN 2363-6084 Series E-ISSN 2363-6092
issn_series 2363-6084
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

书目名称Proceedings of ELM 2021影响因子(影响力)




书目名称Proceedings of ELM 2021影响因子(影响力)学科排名




书目名称Proceedings of ELM 2021网络公开度




书目名称Proceedings of ELM 2021网络公开度学科排名




书目名称Proceedings of ELM 2021被引频次




书目名称Proceedings of ELM 2021被引频次学科排名




书目名称Proceedings of ELM 2021年度引用




书目名称Proceedings of ELM 2021年度引用学科排名




书目名称Proceedings of ELM 2021读者反馈




书目名称Proceedings of ELM 2021读者反馈学科排名




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