Proceedings of ELM-2017

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Proceedings of ELM-2017 by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783030015206
Publisher: Springer International Publishing Publication: October 16, 2018
Imprint: Springer Language: English
Author:
ISBN: 9783030015206
Publisher: Springer International Publishing
Publication: October 16, 2018
Imprint: Springer
Language: English

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.

 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

 

More books from Springer International Publishing

Cover of the book Crowdsourcing of Sensor Cloud Services by
Cover of the book Local Government and Urban Governance in Europe by
Cover of the book Advances in Healthcare Informatics and Analytics by
Cover of the book Handbook of Accessible Instruction and Testing Practices by
Cover of the book Believing in Accordance with the Evidence by
Cover of the book Sustainable Agriculture Reviews by
Cover of the book Regional Integration Processes in the Commonwealth of Independent States by
Cover of the book Camille Flammarion's The Planet Mars by
Cover of the book Modified Au-Based Nanomaterials Studied by Surface Plasmon Resonance Spectroscopy by
Cover of the book Practical Boundary Surveying by
Cover of the book Living Among Giants by
Cover of the book Biochemistry of Oxidative Stress by
Cover of the book Neurorehabilitation for Central Nervous System Disorders by
Cover of the book Geometric Function Theory in Higher Dimension by
Cover of the book Sex Hormones, Exercise and Women by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy