On-Line Learning in Neural Networks

David Saad

ISBN 10: 0521652634 / ISBN 13: 9780521652636

Published by Cambridge University Press, 1999

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9780521652636

Bibliographic Details

• Title: On-Line Learning in Neural Networks
• Publisher: Cambridge University Press
• Publication Date: 1999
• Language: English
• ISBN 10: 0521652634
• ISBN 13: 9780521652636
• Binding: Buch
• Condition: Neu
• Dimensions: 235W x 157H x 29D millimeters 235 millimeters width by 157 millimeters height by 29 millimeters depth
• Weight: 817 grams

About this title

Synopsis

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.

Book Description

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.