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On-Line Learning in Neural Networks by David Saad (Aston University) at Abbey's Bookshop,
On-Line Learning in Neural Networks
— —
David Saad (Aston University)

On-Line Learning in Neural Networks

David Saad (Aston University)

$82.95

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English
Cambridge University Press
30 July 2009
Machine learning; Neural networks & fuzzy systems
Series: Publications of the Newton Institute
On-line learning is one of the most powerful and commonly used techniques for training large layered networks and has been used successfully in many real-world applications. Traditional analytical methods have been recently complemented by ones from statistical physics and Bayesian statistics. This powerful combination of analytical methods provides more insight and deeper understanding of existing algorithms and leads to novel and principled proposals for their improvement. This book presents a coherent picture of the state-of-the-art in the theoretical analysis of on-line learning. An introduction relates the subject to other developments in neural networks and explains the overall picture. Surveys by leading experts in the field combine new and established material and enable non-experts to learn more about the techniques and methods used. This book, the first in the area, provides a comprehensive view of the subject and will be welcomed by mathematicians, scientists and engineers, whether in industry or academia.
Edited by:  
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Volume:   17
Dimensions:   Height: 229mm,  Width: 152mm,  Spine: 23mm
Weight:   600g
ISBN:   9780521117913
ISBN 10:   0521117917
Series:   Publications of the Newton Institute
Pages:   412
Publication Date:  
Audience:   Professional and scholarly ,  Professional and scholarly ,  Undergraduate ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Reviews for On-Line Learning in Neural Networks

Review of the hardback: 'I recommend this book to readers with a theoretical, analytical, or mathematical interest in neural networks, especially online learning.' Computing Reviews I recommend this book to readers with a theoretical, analytical, or mathematical interest in neural networks, especially online learning. Computing Reviews The introduction gives a nice overview of on-line learning in neural networks and relates the subject to other developments in neural networks. The material provides a comprehensive view of the subject and is accessible to mathematicians, statisticians, and engineers in both industry and academia. Journal of the American Statistical Association


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