9783030233068 - proceedings of elm 2018: 11 (14 risultati)
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: Homeless Books, Berlin, GermaniaHomeless Books
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Hardcover. Condizione: Sehr gut. 1. Auflage. Unread book in excellent condition. Language - English. Ships from Berlin.
Lingua: Inglese
Editore: Springer International Publishing, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: moluna, Greven, Germaniamoluna
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Condizione: New.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 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.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 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, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New.
Lingua: Inglese
Editore: Birkhäuser, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 217,46
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 '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. The main theme of ELM2018 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning.This book covers theories, algorithms and applications of ELM. It gives readers a glance at the most recent advances of ELM.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 301,54
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Hardcover. Condizione: Brand New. 356 pages. 9.25x6.10x1.06 inches. In Stock.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condizione: New.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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EUR 371,98
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Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 166,29
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing Jun 2019, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 213,99
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Buch. 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 2018, which was held in Singapore, November 21-23, 2018. This conference provided a forum for academics, researchers and engineers to sh…are 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 '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. The main theme of ELM2018 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning.This book covers theories, algorithms and applications of ELM. It gives readers a glance at the most recent advances of ELM. 356 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Jun 2019, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 213,99
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Buch. 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 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 '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. The main theme of ELM2018 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning.This book covers theories, algorithms and applications of ELM. It gives readers a glance at the most recent advances of ELM.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 356 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 290,57
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 7 di 10 - Proceedings in Adaptation, Learning and Optimization
- Rilegato
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 299,10
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Condizione: New. PRINT ON DEMAND.
