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Proceedings of ELM-2017, Jiuwen Cao; Chi Man Vong; Yoan Miche; Amaury Lenda


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Автор: Jiuwen Cao; Chi Man Vong; Yoan Miche; Amaury Lenda
Название:  Proceedings of ELM-2017
ISBN: 9783030131821
Издательство: Springer
Классификация:


ISBN-10: 3030131823
Обложка/Формат: Soft cover
Страницы: 340
Вес: 0.53 кг.
Дата издания: 2019
Серия: Proceedings in Adaptation, Learning and Optimization
Язык: English
Издание: Softcover reprint of
Иллюстрации: 130 illustrations, black and white; vii, 340 p. 130 illus.
Размер: 234 x 156 x 19
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: Adaptive Control of Vehicle Yaw Rate with Active Steering System and Extreme Learning Machine.- Sparse representation feature for facial expression recognition.- Protecting User Privacy in Mobile Environment using ELM-UPP.- Application Study of Extreme Le



Proceedings of ELM-2017

Автор: Jiuwen Cao; Chi Man Vong; Yoan Miche; Amaury Lenda
Название: Proceedings of ELM-2017
ISBN: 303001519X ISBN-13(EAN): 9783030015190
Издательство: Springer
Рейтинг:
Цена: 30745.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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-2014 Volume 1

Автор: Jiuwen Cao; Kezhi Mao; Erik Cambria; Zhihong Man;
Название: Proceedings of ELM-2014 Volume 1
ISBN: 331936684X ISBN-13(EAN): 9783319366845
Издательство: Springer
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Цена: 26120.00 р.
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Описание: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014.

Proceedings of ELM-2016

Автор: Jiuwen Cao; Erik Cambria; Amaury Lendasse; Yoan Mi
Название: Proceedings of ELM-2016
ISBN: 3319861573 ISBN-13(EAN): 9783319861579
Издательство: Springer
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Цена: 20962.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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. 

Proceedings of ELM 2018

Автор: Jiuwen Cao; Chi Man Vong; Yoan Miche; Amaury Lenda
Название: Proceedings of ELM 2018
ISBN: 3030233065 ISBN-13(EAN): 9783030233068
Издательство: Springer
Рейтинг:
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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.

Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017)

Автор: Paolo Fogliaroni; Andrea Ballatore; Eliseo Clement
Название: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017)
ISBN: 3319639455 ISBN-13(EAN): 9783319639451
Издательство: Springer
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Цена: 30745.00 р.
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Описание: This book presents the proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), which is concerned with all aspects of space and spatial environments as experienced, represented and elaborated by humans, other animals and artificial agents.

Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (Eitrt) 2017: Transportation

Автор: Jia Limin, Qin Yong, Suo Jianguo
Название: Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (Eitrt) 2017: Transportation
ISBN: 9811340366 ISBN-13(EAN): 9789811340369
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The proceedings collect the latest research trends, methods and experimental results in the field of electrical and information technologies for rail transportation. The topics cover novel traction drive technologies of rail transportation, safety technology of rail transportation system, rail transportation information technology, rail transportation operational management technology, rail transportation cutting-edge theory and technology etc. The proceedings can be a valuable reference work for researchers and graduate students working in rail transportation, electrical engineering and information technologies.

Machines, Mechanism and Robotics: Proceedings of Inacomm 2017

Автор: Badodkar D. N., Dwarakanath T. A.
Название: Machines, Mechanism and Robotics: Proceedings of Inacomm 2017
ISBN: 9811341958 ISBN-13(EAN): 9789811341953
Издательство: Springer
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Цена: 9083.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book offers a collection of original peer-reviewed contributions presented at the 3rd International and 18th National Conference on Machines and Mechanisms (iNaCoMM), organized by Division of Remote Handling & Robotics, Bhabha Atomic Research Centre, Mumbai, India, from December 13th to 15th, 2017 (iNaCoMM 2017). It reports on various theoretical and practical features of machines, mechanisms and robotics; the contributions include carefully selected, novel ideas on and approaches to design, analysis, prototype development, assessment and surveys. Applications in machine and mechanism engineering, serial and parallel manipulators, power reactor engineering, autonomous vehicles, engineering in medicine, image-based data analytics, compliant mechanisms, and safety mechanisms are covered. Further papers provide in-depth analyses of data preparation, isolation and brain segmentation for focused visualization and robot-based neurosurgery, new approaches to parallel mechanism-based Master-Slave manipulators, solutions to forward kinematic problems, and surveys and optimizations based on historical and contemporary compliant mechanism-based design. The spectrum of contributions on theory and practice reveals central trends and newer branches of research in connection with these topics.

Proceedings of ELM-2016

Автор: Jiuwen Cao; Erik Cambria; Amaury Lendasse; Yoan Mi
Название: Proceedings of ELM-2016
ISBN: 3319574205 ISBN-13(EAN): 9783319574202
Издательство: Springer
Рейтинг:
Цена: 25155.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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. 

Proceedings of 2017 Chinese Intelligent Systems Conference

Автор: Yingmin Jia; Junping Du; Weicun Zhang
Название: Proceedings of 2017 Chinese Intelligent Systems Conference
ISBN: 9811064989 ISBN-13(EAN): 9789811064982
Издательство: Springer
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Цена: 48913.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The topics covered include Multi-agent system, Evolutionary Computation, Artificial Intelligence, Complex systems, Computation intelligence and soft computing, Intelligent control, Advanced control technology, Robotics and applications, Intelligent information processing, Iterative learning control, Machine Learning, and etc.

Proceedings of the Ninth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2017)

Автор: Abraham
Название: Proceedings of the Ninth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2017)
ISBN: 3319763563 ISBN-13(EAN): 9783319763569
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book presents 18 carefully selected papers from the ninth edition of the International Conference on Soft Computing and Pattern Recognition (SoCPaR 2017), which was held in Marrakesh, Morocco from December 11 to 13, 2017.

Proceedings of ELM-2015 Volume 2

Автор: Jiuwen Cao; Kezhi Mao; Jonathan Wu; Amaury Lendass
Название: Proceedings of ELM-2015 Volume 2
ISBN: 3319283723 ISBN-13(EAN): 9783319283722
Издательство: Springer
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Цена: 32652.00 р.
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Описание: This book contains some selected papersfrom the International Conference on Extreme Learning Machine 2015,which was held in Hangzhou, China,December 15-17,2015.

Proceedings of ELM-2015 Volume 1

Автор: Jiuwen Cao; Kezhi Mao; Jonathan Wu; Amaury Lendass
Название: Proceedings of ELM-2015 Volume 1
ISBN: 3319283960 ISBN-13(EAN): 9783319283968
Издательство: Springer
Рейтинг:
Цена: 32652.00 р.
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Описание: This book contains some selected papersfrom the International Conference on Extreme Learning Machine 2015,which was held in Hangzhou, China,December 15-17,2015.


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