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Extreme Learning Machines 2013: Algorithms and Applications (Paperback, Softcover reprint of the original 1st ed. 2014)
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Extreme Learning Machines 2013: Algorithms and Applications (Paperback, Softcover reprint of the original 1st ed. 2014)
Series: Adaptation, Learning, and Optimization, 16
Expected to ship within 10 - 15 working days
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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.
General
Imprint: |
Springer International Publishing AG
|
Country of origin: |
Switzerland |
Series: |
Adaptation, Learning, and Optimization, 16 |
Release date: |
September 2016 |
First published: |
2014 |
Editors: |
Fuchen Sun
• Kar-Ann Toh
• Manuel Grana Romay
• Kezhi Mao
|
Dimensions: |
235 x 155 x 12mm (L x W x T) |
Format: |
Paperback
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Pages: |
225 |
Edition: |
Softcover reprint of the original 1st ed. 2014 |
ISBN-13: |
978-3-319-35003-5 |
Categories: |
Books >
Computing & IT >
General
|
LSN: |
3-319-35003-X |
Barcode: |
9783319350035 |
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