Miche yoan (39 Ergebnisse)
Sprache: Englisch
Verlag: Springer 2019
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer 2021
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer 2017
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Verlag: Springer International Publishing 2018
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
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Gebunden. Zustand: New.
Weitere BilderSprache: Englisch
Verlag: Springer 2021
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 von 10 - Proceedings in Adaptation, Learning and Optimization
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Taschenbuch. Zustand: Neu. Proceedings of ELM2019 | Jiuwen Cao (u. a.) | Taschenbuch | vi | Englisch | 2021 | Springer | EAN 9783030590499 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Weitere BilderSprache: Englisch
Verlag: Springer 2018
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
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Taschenbuch. Zustand: Neu. Proceedings of ELM-2016 | Jiuwen Cao (u. a.) | Taschenbuch | 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 2021
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 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 2019, which was held in Yangzhou, China, December 14-16, 2019. Extreme Learning Machines (ELMs) aim to enable pervasive learning and pervasive intel…ligence. 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 ELM2019 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning.This conference provides 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.This book covers theories, algorithms and applications of ELM. It gives readers a glance of the most recent advances of ELM.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing 2018
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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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 International Publishing 2017
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. Buch 5 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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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.
Proceedings of Elm2019
Cao, Jiuwen (Editor)/ Vong, Chi Man (Editor)/ Miche, Yoan (Editor)/ Lendasse, Amaury (Editor)
Sprache: Englisch
Verlag: Springer Nature 2021
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Paperback. Zustand: Brand New. 188 pages. 9.25x6.10x0.45 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing 2019
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 6 von 10. Buch 6 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
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Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 von 10 - Proceedings in Adaptation, Learning and Optimization
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Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
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Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
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Serie: Proceedings in Adaptation, Learning and Optimization, Buch 6 von 10. Buch 6 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer 2020
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer 2020
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
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Sprache: Englisch
Verlag: Springer 2019
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
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Verlag: Springer 2018
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 6 von 10. Buch 6 von 10 - Proceedings in Adaptation, Learning and Optimization
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Serie: Proceedings in Adaptation, Learning and Optimization, Buch 10 von 10. Buch 10 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 2019, which was held in Yangzhou, China, December 14-16, 2019. Extreme Learning Machines (ELMs) aim 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 ELM2019 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning.This conference provides 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.This book covers theories, algorithms and 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: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. 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: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. 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: Proceedings in Adaptation, Learning and Optimization, Buch 5 von 10. 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.
Weitere BilderSprache: Englisch
Verlag: Springer 2019
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 6 von 10. Buch 6 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Taschenbuch. Zustand: Neu. Proceedings of ELM-2017 | Jiuwen Cao (u. a.) | Taschenbuch | vii | Englisch | 2019 | Springer | EAN 9783030131821 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Weitere BilderSprache: Englisch
Verlag: Springer 2020
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
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Taschenbuch. Zustand: Neu. Proceedings of ELM 2018 | Jiuwen Cao (u. a.) | Taschenbuch | viii | Englisch | 2020 | Springer | EAN 9783030233099 | 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 2019
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 6 von 10. Buch 6 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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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 (ELM) 2017, held in Yantai, China, October 4-7, 2017. The book covers theories, algorithms and applications of ELM.Extreme Learning Machines (ELM) a…ims 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.
Sprache: Englisch
Verlag: Springer International Publishing 2020
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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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 2018, which was held in Singapore, November 21-23, 2018. This conference provided a forum for academics, researchers and engineers to share and exch…ange 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.
Sprache: Englisch
Verlag: Springer International Publishing 2019
Serie: Proceedings in Adaptation, Learning and Optimization, Buch 7 von 10. Buch 7 von 10 - Proceedings in Adaptation, Learning and Optimization
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 213,99
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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 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.
