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
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Feb2215580243831
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521117913
Quantité disponible : 1 disponible(s)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780521117913_new
Quantité disponible : Plus de 20 disponibles
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 1st edition. 408 pages. 8.90x5.98x1.18 inches. In Stock. This item is printed on demand. N° de réf. du vendeur __0521117917
Quantité disponible : 1 disponible(s)
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9780521117913
Quantité disponible : Plus de 20 disponibles
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 412. N° de réf. du vendeur 26535497
Quantité disponible : 4 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 412 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. N° de réf. du vendeur 8360982
Quantité disponible : 4 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. N° de réf. du vendeur C9780521117913
Quantité disponible : Plus de 20 disponibles
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 412. N° de réf. du vendeur 18535491
Quantité disponible : 4 disponible(s)
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780521117913
Quantité disponible : 1 disponible(s)