9783030131821 - proceedings of elm-2017: 10 (11 risultati)
Lingua: Inglese
Editore: Springer International Publishing, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Condizione: New.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Condizione: New. In.
Altre immaginiLingua: Inglese
Editore: Springer, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Proceedings of ELM-2017 | Jiuwen Cao (u. a.) | Taschenbuch | Proceedings in Adaptation, Learning and Optimization | vii | Englisch | 2019 | Springer | EAN 9783030131821 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[do…t]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Condizione: New.
Lingua: Inglese
Editore: Springer International Publishing, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 213,99
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 learning systems. ELM theories and algorithms argue that 'random hidden neurons' capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers.This conference will provide 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.It gives readers a glance of the most recent advances of ELM.
Proceedings of Elm-2017
Cao, Jiuwen (Editor)/ Vong, Chi Man (Editor)/ Miche, Yoan (Editor)/ Lendasse, Amaury (Editor)
Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. reprint edition. 350 pages. 9.25x6.10x0.73 inches. In Stock.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condizione: New.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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Paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing Dez 2019, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 Learni…ng 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 learning systems. ELM theories and algorithms argue that 'random hidden neurons' capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers.This conference will provide 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.It gives readers a glance of the most recent advances of ELM. 348 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Dez 2019, 2019
Serie: Libro 6 di 10 - Proceedings in Adaptation, Learning and Optimization
- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 213,99
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 M…achines (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 learning systems. ELM theories and algorithms argue that 'random hidden neurons' capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers.This conference will provide 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.It gives readers a glance of the most recent advances of ELM.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 348 pp. Englisch.
