| 書(shū)目名稱(chēng) | Proceedings of ELM 2018 |
| 編輯 | Jiuwen Cao,Chi Man Vong,Amaury Lendasse |
| 視頻video | http://file.papertrans.cn/758/757557/757557.mp4 |
| 概述 | Provides recent research on Extreme Learning Machines (ELM).Contains selected papers from the International Conference on Extreme Learning Machines 2018, which was held in Singapore, November 21–23, 2 |
| 叢書(shū)名稱(chēng) | Proceedings in Adaptation, Learning and Optimization |
| 圖書(shū)封面 |  |
| 描述 | .This book contains some selected papers from the International Conference on Extreme Learning Machine 2018, which was held in Singapore, November 21–23, 2018. This conference provided a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning..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 “l(fā)earning 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, independe |
| 出版日期 | Conference proceedings 2020 |
| 關(guān)鍵詞 | Intelligent Systems; Extreme Learning Machines; ELM 2018; The International Conference on Extreme Learn |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-23307-5 |
| isbn_softcover | 978-3-030-23309-9 |
| isbn_ebook | 978-3-030-23307-5Series ISSN 2363-6084 Series E-ISSN 2363-6092 |
| issn_series | 2363-6084 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手機(jī)版|小黑屋|
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