Proceedings elm 2016 (26 Ergebnisse)
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Proceedings of Elm-2016
Cao, Jiuwen (EDT); Cambria, Erik (EDT); Lendasse, Amaury (EDT); Miche, Yoan (EDT); Vong, Chi Man (EDT)
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Proceedings of Elm-2016
Cao, Jiuwen (EDT); Cambria, Erik (EDT); Lendasse, Amaury (EDT); Miche, Yoan (EDT); Vong, Chi Man (EDT)
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Proceedings of Elm-2016
Cao, Jiuwen (EDT); Cambria, Erik (EDT); Lendasse, Amaury (EDT); Miche, Yoan (EDT); Vong, Chi Man (EDT)
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Sprache: Englisch
Verlag: Springer International Publishing, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
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Proceedings of Elm-2016
Cao, Jiuwen (EDT); Cambria, Erik (EDT); Lendasse, Amaury (EDT); Miche, Yoan (EDT); Vong, Chi Man (EDT)
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Weitere BilderSprache: Englisch
Verlag: Springer, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Taschenbuch. Zustand: Neu. Proceedings of ELM-2016 | Jiuwen Cao (u. a.) | Taschenbuch | Proceedings in Adaptation, Learning and Optimization | xiii | Englisch | 2018 | Springer | EAN 9783319861579 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]…com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains some selected papers from the International Conference on Extreme Learning Machine 2016, which was held in Singapore, December13-15, 2016. This conference will provide a forum for academics, researchers and engineers to share and e…xchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neurosciencesuggests 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large-scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains some selected papers from the International Conference on Extreme Learning Machine 2016, which was held in Singapore, December13-15, 2016. 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. Extreme Learning Machines (ELM) aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neurosciencesuggests 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large-scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Paperback. Zustand: Brand New. reprint edition. 285 pages. 9.25x6.10x0.98 inches. In Stock.
Sprache: Englisch
Verlag: Palgrave Macmillan, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 300 | Sprache: Englisch | Produktart: Bücher | This book contains some selected papers from the International Conference on Extreme Learning Machine 2016, which was held in Singapore, December13-15, 2016. This conference will provide a forum for academics, researchers and en…gineers 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 break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neurosciencesuggests 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large¿scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Hardcover. Zustand: Brand New. 298 pages. 9.25x6.10x0.79 inches. In Stock.
Sprache: Englisch
Verlag: Springer, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Sprache: Englisch
Verlag: Springer International Publishing Mai 2017, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Buch. Zustand: 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 2016, which was held in Singapore, December 13-15, 2016. This conference will provide a forum for academics, researchers and engineers to s…hare 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 break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large-scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM. 300 pp. Englisch.
Sprache: Englisch
Verlag: Springer International Publishing Mai 2018, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
- Print-on-Demand
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, DeutschlandBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Zustand: 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 2016, which was held in Singapore, December 13-15, 2016. This conference will provide a forum for academics, researchers and enginee…rs 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 break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large-scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM. 300 pp. Englisch.
Sprache: Englisch
Verlag: Springer, Springer Mai 2018, 2018
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
- Print-on-Demand
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Taschenbuch. Zustand: 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 2016, which was held in Singapore, December13-15, 2016. 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. Extreme Learning Machines (ELM) aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELMrepresents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neurosciencesuggests 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large¿scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 300 pp. Englisch.
Sprache: Englisch
Verlag: Springer, Springer Mai 2017, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
- Print-on-Demand
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Buch. Zustand: 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 2016, which was held in Singapore, December13-15, 2016. 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. Extreme Learning Machines (ELM) aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELMrepresents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neurosciencesuggests 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. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large¿scale computing and artificial intelligence.This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 300 pp. Englisch.
Sprache: Englisch
Verlag: Springer, 2017
Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
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Serie: Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
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