Proceedings of ELM-2016, Jiuwen Cao; Erik Cambria; Amaury Lendasse; Yoan Mi
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.
Автор: Jiuwen Cao; Chi Man Vong; Yoan Miche; Amaury Lenda Название: Proceedings of ELM-2017 ISBN: 3030131823 ISBN-13(EAN): 9783030131821 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 (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.
Автор: Jiuwen Cao; Kezhi Mao; Erik Cambria; Zhihong Man; Название: Proceedings of ELM-2014 Volume 1 ISBN: 331936684X ISBN-13(EAN): 9783319366845 Издательство: Springer Рейтинг: Цена: 26120.00 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 2014, which was held in Singapore, December 8-10, 2014.
Автор: Jiuwen Cao; Kezhi Mao; Erik Cambria; Zhihong Man; Название: Proceedings of ELM-2014 Volume 2 ISBN: 3319366858 ISBN-13(EAN): 9783319366852 Издательство: Springer Рейтинг: Цена: 26120.00 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 2014, which was held in Singapore, December 8-10, 2014.
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.
Описание: This four volume set of books constitutes the proceedings of the 2016 37th International Conference Information Systems Architecture and Technology (ISAT), or ISAT 2016 for short, held on September 18–20, 2016 in Karpacz, Poland. The conference was organized by the Department of Management Systems and the Department of Computer Science, Wroc?aw University of Science and Technology, Poland. The papers included in the proceedings have been subject to a thorough review process by highly qualified peer reviewers. The accepted papers have been grouped into four parts:Part I—addressing topics including, but not limited to, systems analysis and modeling, methods for managing complex planning environment and insights from Big Data research projects.Part II—discoursing about topics including, but not limited to, Web systems, computer networks, distributed computing, and multi-agent systems and Internet of Things.Part III—discussing topics including, but not limited to, mobile and Service Oriented Architecture systems, high performance computing, cloud computing, knowledge discovery, data mining and knowledge based management.Part IV—dealing with topics including, but not limited to, finance, logistics and market problems, and artificial intelligence methods.
Описание: This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21-23, 2016 in Marrakech, Morocco.
The 2016 International Conference on Artificial Intelligence Science and Technology (AIST2016) was held in Shanghai, China, from 15th to 17th July, 2016.
AIST2016 aims to bring together researchers, engineers, and students to the areas of Artificial Intelligence Science and Technology. AIST2016 features unique mixed topics of artificial intelligence and application, computer and software, communication and network, information and security, data mining, and optimization.
This volume consists of 101 peer-reviewed articles by local and foreign eminent scholars which cover the frontiers and state-of-art development in AI Technology.
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.
Описание: This four volume set of books constitutes the proceedings of the 2016 37th International Conference Information Systems Architecture and Technology (ISAT), or ISAT 2016 for short, held on September 18–20, 2016 in Karpacz, Poland. The conference was organized by the Department of Management Systems and the Department of Computer Science, Wroc?aw University of Science and Technology, Poland. The papers included in the proceedings have been subject to a thorough review process by highly qualified peer reviewers. The accepted papers have been grouped into four parts:Part I—addressing topics including, but not limited to, systems analysis and modeling, methods for managing complex planning environment and insights from Big Data research projects.Part II—discoursing about topics including, but not limited to, Web systems, computer networks, distributed computing, and mulit-agent systems and Internet of Things.Part III—discussing topics including, but not limited to, mobile and Service Oriented Architecture systems, high performance computing, cloud computing, knowledge discovery, data mining and knowledge based management.Part IV—dealing with topics including, but not limited to, finance, logistics and market problems, and artificial intelligence methods.
Описание: This four volume set of books constitutes the proceedings of the 2016 37th International Conference Information Systems Architecture and Technology (ISAT), or ISAT 2016 for short, held on September 18–20, 2016 in Karpacz, Poland. The conference was organized by the Department of Management Systems and the Department of Computer Science, Wroc?aw University of Science and Technology, Poland. The papers included in the proceedings have been subject to a thorough review process by highly qualified peer reviewers. The accepted papers have been grouped into four parts:Part I—addressing topics including, but not limited to, systems analysis and modeling, methods for managing complex planning environment and insights from Big Data research projects.Part II—discoursing about topics including, but not limited to, Web systems, computer networks, distributed computing, and mulit-agent systems and Internet of Things.Part III—discussing topics including, but not limited to, mobile and Service Oriented Architecture systems, high performance computing, cloud computing, knowledge discovery, data mining and knowledge based management.Part IV—dealing with topics including, but not limited to, finance, logistics and market problems, and artificial intelligence methods.
Описание: This four volume set of books constitutes the proceedings of the 2016 37th International Conference Information Systems Architecture and Technology (ISAT), or ISAT 2016 for short, held on September 18–20, 2016 in Karpacz, Poland. The conference was organized by the Department of Management Systems and the Department of Computer Science, Wroc?aw University of Science and Technology, Poland. The papers included in the proceedings have been subject to a thorough review process by highly qualified peer reviewers. The accepted papers have been grouped into four parts:Part I—addressing topics including, but not limited to, systems analysis and modeling, methods for managing complex planning environment and insights from Big Data research projects.Part II—discoursing about topics including, but not limited to, Web systems, computer networks, distributed computing, and mulit-agent systems and Internet of Things.Part III—discussing topics including, but not limited to, mobile and Service Oriented Architecture systems, high performance computing, cloud computing, knowledge discovery, data mining and knowledge based management.Part IV—dealing with topics including, but not limited to, finance, logistics and market problems, and artificial intelligence methods.
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