Edited volume written by leading experts providing state-of-art survey in on-line learning and neural networks.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
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
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Hardcover. Etat : Near fine. Publications of the Newton Institute. x, 398 p. 24 cm. Ink signature. N° de réf. du vendeur 149295
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Hardcover. Etat : new. Hardcover. 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. On-line learning is one of the most commonly used techniques for training large layered networks. This book presents a picture of the state-of-the-art in the subject. An introduction relates it to other developments in neural networked and explains the overall picture. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521652636
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Hardcover. Etat : Brand New. 398 pages. 9.50x6.50x1.25 inches. In Stock. This item is printed on demand. N° de réf. du vendeur __0521652634
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Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
Etat : New. Edited volume written by leading experts providing state-of-art survey in on-line learning and neural networks. Editor(s): Saad, David. Series: Publications of the Newton Institute. Num Pages: 412 pages, 40 b/w illus. BIC Classification: UYQN. Category: (P) Professional & Vocational. Dimension: 235 x 159 x 31. Weight in Grams: 2362. . 1999. Illustrated. hardcover. . . . . N° de réf. du vendeur V9780521652636
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