On-Line Learning in Neural Networks: Publications of the Newton Institute, cartea 17
Editat de David Saaden Limba Engleză Paperback – 29 iul 2009
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 327.13 lei 6-8 săpt. | |
Cambridge University Press – 29 iul 2009 | 327.13 lei 6-8 săpt. | |
Hardback (1) | 979.59 lei 6-8 săpt. | |
Cambridge University Press – 27 ian 1999 | 979.59 lei 6-8 săpt. |
Din seria Publications of the Newton Institute
- Preț: 448.86 lei
- 14% Preț: 1076.30 lei
- 11% Preț: 425.94 lei
- 20% Preț: 644.44 lei
- 11% Preț: 430.94 lei
- 20% Preț: 303.67 lei
- 14% Preț: 1488.13 lei
- 14% Preț: 789.17 lei
- Preț: 430.14 lei
- Preț: 429.67 lei
- Preț: 403.44 lei
- 20% Preț: 773.34 lei
- 11% Preț: 486.85 lei
- 11% Preț: 490.59 lei
- 11% Preț: 491.66 lei
- 14% Preț: 794.45 lei
- 14% Preț: 1147.20 lei
Preț: 327.13 lei
Preț vechi: 408.91 lei
-20% Nou
Puncte Express: 491
Preț estimativ în valută:
62.60€ • 65.28$ • 52.03£
62.60€ • 65.28$ • 52.03£
Carte tipărită la comandă
Livrare economică 20 martie-03 aprilie
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780521117913
ISBN-10: 0521117917
Pagini: 412
Ilustrații: 40 b/w illus.
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.6 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Seria Publications of the Newton Institute
Locul publicării:Cambridge, United Kingdom
ISBN-10: 0521117917
Pagini: 412
Ilustrații: 40 b/w illus.
Dimensiuni: 152 x 229 x 23 mm
Greutate: 0.6 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Seria Publications of the Newton Institute
Locul publicării:Cambridge, United Kingdom
Cuprins
Foreword C. Bishop; 1. Introduction D. Saad; 2. On-line learning and stochastic approximations Léon Bottou; 3. Exact and perturbative solutions for the ensemble dynamics Todd Leen; 4. A statistical study of on-line learning Noboru Murata; 5. On-line learning in switching and drifting environments Klaus-Robert Mueller, Andreas Ziehe, Noboru Murata and Shun-ichi Amari; 6. Parameter adaptation in stochastic optimization Luis B. Almeida, Thibault Langlois, José D. Amaral and Alexander Plakhov; 7. Optimal on-line learning for multilayer neural networks David Saad and Magnus Rattray; 8. Universal asymptotics in committee machines with tree architecture Mauro Copelli and Nestor Caticha; 9. Incorporating curvature information in on-line learning Magnus Rattray and David Saad; 10. Annealed on-line learning in multilayer networks Siegfried Bös and Shun-ichi Amari; 11. On-line learning of prototypes and principal components Michael Biehl, Ansgar Freking, Matthias Hölzer, Georg Reents and Enno Schlösser; 12. On-line learning with time-correlated patterns Tom Heskes and Wim Wiegerinck; 13. On-line learning from finite training sets David Barber and Peter Sollich; 14. Dynamics of supervised learning with restricted training sets Anthony C. C. Coolen and David Saad; 15. On-line learning of a decision boundary with and without queries Yoshiyuki Kabashima and Shigeru Shinomoto; 16. A Bayesian approach to on-line learning Manfred Opper; 17. Optimal perception learning: an on-line Bayesian approach Sara A. Solla and Ole Winther.
Recenzii
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
Descriere
Edited volume written by leading experts providing state-of-art survey in on-line learning and neural networks.