On-Line Learning in Neural Networks (Publications of the Newton Institute)

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9780521117913: On-Line Learning in Neural Networks (Publications of the Newton Institute)

On-line learning is one of the most commonly used techniques for training neural networks. Though it has been used successfully in many real-world applications, most training methods are based on heuristic observations. The lack of theoretical support damages the credibility as well as the efficiency of neural networks training, making it hard to choose reliable or optimal methods. 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 nonexperts 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, both in industry and academia.

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On-line learning is one of the most commonly used techniques for training neural networks, and has been used successfully in many real-world applications. The aim of this book is to present a coherent picture of the state-of-the-art in on-line learning. An introduction relates the subject to other developments in neural networks and explains the overall picture. There follow surveys by leading experts in the field that combine new and established material and enable non-experts to learn more about the techniques and methods used.

Review:

"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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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2009. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****.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. Bookseller Inventory # AAV9780521117913

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Published by CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2009)
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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2009. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****. 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. Bookseller Inventory # AAV9780521117913

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Book Description Cambridge University Press. Paperback. Book Condition: New. 412 pages. Dimensions: 8.9in. x 6.0in. x 1.2in.On-line learning is one of the most commonly used techniques for training neural networks. Though it has been used successfully in many real-world applications, most training methods are based on heuristic observations. The lack of theoretical support damages the credibility as well as the efficiency of neural networks training, making it hard to choose reliable or optimal methods. 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 nonexperts 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, both in industry and academia. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9780521117913

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