Algebraic Geometry and Statistical Learning Theory |
|
| Author:
| Watanabe, Sumio |
| Series title: | Cambridge Monographs on Applied and Computational Mathematics Ser. |
| ISBN: | 978-0-521-86467-1 |
| Publication Date: | Aug 2009 |
| Publisher: | Cambridge University Press
|
| Book Format: | Hardback |
| List Price: | AUD $129.95 |
Book Description:
|
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.
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.