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Advances In Extreme Learning Machines
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Book Synopsis Extreme Learning Machines 2013: Algorithms and Applications by : Fuchen Sun
Download or read book Extreme Learning Machines 2013: Algorithms and Applications written by Fuchen Sun and published by Springer. This book was released on 2014-07-08 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability. This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discussions of “learning without iterative tuning". This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM.
Book Synopsis Advances in Extreme Learning Machines (ELM 2014) by : Guang Bin Huang
Download or read book Advances in Extreme Learning Machines (ELM 2014) written by Guang Bin Huang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Contains Special Issue Articles: Advances in Extreme Learning Machine by :
Download or read book Contains Special Issue Articles: Advances in Extreme Learning Machine written by and published by . This book was released on 2014 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Recent Trends in Information and Communication Technology by : Faisal Saeed
Download or read book Recent Trends in Information and Communication Technology written by Faisal Saeed and published by Springer. This book was released on 2017-05-24 with total page 931 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents 94 papers from the 2nd International Conference of Reliable Information and Communication Technology 2017 (IRICT 2017), held in Johor, Malaysia, on April 23–24, 2017. Focusing on the latest ICT innovations for data engineering, the book presents several hot research topics, including advances in big data analysis techniques and applications; mobile networks; applications and usability; reliable communication systems; advances in computer vision, artificial intelligence and soft computing; reliable health informatics and cloud computing environments, e-learning acceptance models, recent trends in knowledge management and software engineering; security issues in the cyber world; as well as society and information technology.
Book Synopsis Special Issue: Advances in Extreme Learning Machine by : International Workshop of Extreme Learning Machines. 2010, Adelaide
Download or read book Special Issue: Advances in Extreme Learning Machine written by International Workshop of Extreme Learning Machines. 2010, Adelaide and published by . This book was released on 2011 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Special Issue: Advances in Extreme Learning Machines (ELM 2011) by : Guangbing Huang
Download or read book Special Issue: Advances in Extreme Learning Machines (ELM 2011) written by Guangbing Huang and published by . This book was released on 2013 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of ELM-2014 Volume 2 by : Jiuwen Cao
Download or read book Proceedings of ELM-2014 Volume 2 written by Jiuwen Cao and published by Springer. This book was released on 2014-12-09 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.
Book Synopsis Advances in Extreme Learning Machine by :
Download or read book Advances in Extreme Learning Machine written by and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of ELM 2018 by : Jiuwen Cao
Download or read book Proceedings of ELM 2018 written by Jiuwen Cao and published by Springer. This book was released on 2019-06-29 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Advances in Extreme Learning Machine (ELM 2011) by :
Download or read book Advances in Extreme Learning Machine (ELM 2011) written by and published by . This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Extreme Learning Machines by : Guangbing Huang
Download or read book Advances in Extreme Learning Machines written by Guangbing Huang and published by . This book was released on 2014 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pathological Brain Detection by : Shui-Hua Wang
Download or read book Pathological Brain Detection written by Shui-Hua Wang and published by Springer. This book was released on 2018-07-20 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer’s detection, multiple sclerosis detection, etc.
Book Synopsis Special Issue: Advances in Extreme Learning Machines (ELM 2011) by : Guangbing Huang
Download or read book Special Issue: Advances in Extreme Learning Machines (ELM 2011) written by Guangbing Huang and published by . This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of ELM 2021 by : Kaj-Mikael Björk
Download or read book Proceedings of ELM 2021 written by Kaj-Mikael Björk and published by Springer Nature. This book was released on 2023-01-18 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains papers from the International Conference on Extreme Learning Machine 2021, which was held in virtual on December 15–16, 2021. 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 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.
Book Synopsis Proceedings of ELM-2015 Volume 2 by : Jiuwen Cao
Download or read book Proceedings of ELM-2015 Volume 2 written by Jiuwen Cao and published by Springer. This book was released on 2016-01-02 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.
Book Synopsis Proceedings of ELM-2014 Volume 1 by : Jiuwen Cao
Download or read book Proceedings of ELM-2014 Volume 1 written by Jiuwen Cao and published by Springer. This book was released on 2014-12-04 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.
Book Synopsis Proceedings of ELM2019 by : Jiuwen Cao
Download or read book Proceedings of ELM2019 written by Jiuwen Cao and published by Springer Nature. This book was released on 2020-09-11 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
