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Author: Keen J. Babbage Publisher: R&L Education ISBN: 9781578861408 Category : Education Languages : en Pages : 218
Book Description
Keen Babbage shows educators how to cause extreme learning in the classroom while also creating a classroom learning community in which the teacher and the student team up in a vibrant, symbiotic, fulfilling partnership.
Author: Keen J. Babbage Publisher: R&L Education ISBN: 9781578861408 Category : Education Languages : en Pages : 218
Book Description
Keen Babbage shows educators how to cause extreme learning in the classroom while also creating a classroom learning community in which the teacher and the student team up in a vibrant, symbiotic, fulfilling partnership.
Author: Jiuwen Cao Publisher: Springer ISBN: 3030233073 Category : Technology & Engineering Languages : en Pages : 356
Book Description
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.
Author: Management Association, Information Resources Publisher: IGI Global ISBN: 1799824616 Category : Science Languages : en Pages : 1961
Book Description
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.
Author: Jiuwen Cao Publisher: Springer Nature ISBN: 3030589897 Category : Technology & Engineering Languages : en Pages : 189
Book Description
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.
Author: Shui-Hua Wang Publisher: Springer ISBN: 9811040265 Category : Computers Languages : en Pages : 237
Book Description
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.
Author: Pandian Vasant Publisher: Springer ISBN: 3030009793 Category : Technology & Engineering Languages : en Pages : 588
Book Description
This book includes innovative research work presented at ICO’2018, the 1st International Conference on Intelligent Computing and Optimization, held in Pattaya, Thailand on October 4–5, 2018. The conference presented topics ranging from power quality, reliability, security assurance, cloud computing, smart cities, renewable energy, agro-engineering, smart vehicles, deep learning, block chain, power systems, AI, machine learning, manufacturing systems, and big-data analytics. This volume focuses on subjects related to innovative computing, uncertainty management and optimization approaches to real-world problems in big-data, smart cities, sustainability, meta-heuristics, cyber-security, IoTs, economics and finance, renewable energy, energy and electricity systems, and block chain. Presenting cutting-edge methodologies with real-world application problems and their solutions, the book is useful for researchers, managers, executives, students, academicians, practicing scientists, and decision makers from all around the globe. It offers the academic and the applied communities a compendium and a research resource with significant insights and inspiration for innovative scientific education, investigation and collaboration, to overcome “hard problems” among the emerging challenges today and in the future.
Author: Amy C. Edmondson Publisher: Emerald Group Publishing ISBN: 1786354500 Category : Business & Economics Languages : en Pages : 224
Book Description
Extreme Teaming provides new insights into the world of increasingly complex, cross industry projects. Amy Edmondson and Jean-Francois Harvey show vividly through their international cases how the complex demands of collaboration impact on management and revolutionize our understanding of teams.
Author: Sabri Arik Publisher: Springer ISBN: 3319265326 Category : Computers Languages : en Pages : 758
Book Description
The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.
Author: Jiuwen Cao Publisher: Springer ISBN: 3030015203 Category : Technology & Engineering Languages : en Pages : 347
Book Description
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.
Author: Jiuwen Cao Publisher: Springer ISBN: 3319140639 Category : Technology & Engineering Languages : en Pages : 446
Book Description
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.
Author: Keen J. Babbage
Author: Keen J. Babbage
Author: Jiuwen Cao
Author: Management Association, Information Resources
Author: Jiuwen Cao
Author: Shui-Hua Wang
Author: Pandian Vasant
Author: Amy C. Edmondson
Author: Sabri Arik
Author: Jiuwen Cao
Author: Jiuwen Cao