| 書目名稱 | Proceedings of ELM-2017 | | 編輯 | Jiuwen Cao,Chi Man Vong,Amaury Lendasse | | 視頻video | http://file.papertrans.cn/758/757565/757565.mp4 | | 概述 | Provides recent research on Extreme Learning Machine.Includes selected papers from the International Conference on Extreme Learning Machine 2017, which was held in Yantai, China, October 4–7, 2017.Pre | | 叢書名稱 | Proceedings in Adaptation, Learning and Optimization | | 圖書封面 |  | | 描述 | .This book contains some selected papers from the International Conference on Extreme Learning Machine (ELM) 2017, held in Yantai, China, October 4–7, 2017. The book covers theories, algorithms and applications of ELM..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 data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learni | | 出版日期 | Conference proceedings 2019 | | 關(guān)鍵詞 | Intelligent Systems; Extreme Learning Machines; Multiagent Systems; ELM 2017; The International Conferen | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-01520-6 | | isbn_softcover | 978-3-030-13182-1 | | isbn_ebook | 978-3-030-01520-6Series 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 |
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