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Forventes på lager: 13-08-2009
Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory. Many widely used statistical models are singular: mixture models, neural networks, HMMs, and Bayesian networks are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
| Forlag | Cambridge University Press |
| Forfatter | Sumio (Tokyo Institute of Technology) Watanabe |
| Type | Bog |
| Format | Hardback |
| Sprog | Engelsk |
| Udgivelsesdato | 13-08-2009 |
| Første udgivelsesår | 2009 |
| Serie | Cambridge Monographs on Applied and Computational Mathematics |
| Illustrationer | Worked examples or Exercises; 13 Halftones, unspecified |
| Originalsprog | United Kingdom |
| Sideantal | 300 |
| Indbinding | Hardback |
| Forlag | Cambridge University Press |
| Sideoplysninger | 300 pages, Worked examples or Exercises; 13 Halftones, unspecified |
| Mål | 237 x 159 x 21 |
| ISBN-13 / EAN-13 | 9780521864671 |