Articles liés à Proceedings of ELM-2016
Synopsis
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.
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- ÉditeurSpringer
- Date d'édition2018
- ISBN 10 3319861573
- ISBN 13 9783319861579
- ReliureBroché
- Langueanglais
- Nombre de pages300
- ÉditeurCao Jiuwen, Cambria Erik, Lendasse Amaury, Miche Yoan, Vong Chi Man
- Coordonnées du fabricantnon disponible
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Proceedings of ELM-2016: 9 (Proceedings in Adaptation, Learning and Optimization, 9)
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Springer, 2018
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
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Proceedings of ELM-2016
Edité par
Springer International Publishing, 2018
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
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Proceedings of ELM-2016
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Springer International Publishing, 2018
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
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Proceedings of ELM-2016
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783319861579
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Proceedings of ELM-2016
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Springer International Publishing Mai 2018, 2018
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
Neuf
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Taschenbuch. Etat : 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 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. N° de réf. du vendeur 9783319861579
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Proceedings of ELM-2016 (Proceedings in Adaptation, Learning and Optimization, 9)
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Proceedings of ELM-2016
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 300 pp. Englisch. N° de réf. du vendeur 9783319861579
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Proceedings of ELM-2016 (Proceedings in Adaptation, Learning and Optimization, 9)
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Proceedings of Elm-2016
Edité par
Springer-Verlag New York Inc, 2018
ISBN 10 : 3319861573
ISBN 13 : 9783319861579
Neuf
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Paperback. Etat : Brand New. reprint edition. 285 pages. 9.25x6.10x0.98 inches. In Stock. N° de réf. du vendeur x-3319861573
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Proceedings of ELM-2016 (Proceedings in Adaptation, Learning and Optimization)
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Etat : New. pp. 285. N° de réf. du vendeur 26375745469
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