On-line learning is one of the most commonly used techniques for training large layered networks. Traditional methods have been recently complemented by ones from statistical physics and Bayesian statistics to provide more insight and deeper understanding of existing algorithms. This book presents a coherent picture of the state-of-the-art.
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Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.
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Hardcover. Condición: Very Good. On-Line Learning in Neural Networks: 17 (Publications of the Newton Institute, Series Number 17) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. Nº de ref. del artículo: 7719-9780521652636
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Condición: 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. . . . . Nº de ref. del artículo: V9780521652636
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. On-line learning is one of the most commonly used techniques for training large layered networks. Traditional methods have been recently complemented by ones from statistical physics and Bayesian statistics to provide more insight and deeper understanding o. Nº de ref. del artículo: 446943904
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Hardcover. Condición: 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9780521652636
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