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Algebraic Geometry and Statistical Learning Theory - Cambridge Monographs on Applied and Computational Mathematics Watanabe, Sumio (Tokyo Institute of Technology)
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Algebraic Geometry and Statistical Learning Theory - Cambridge Monographs on Applied and Computational Mathematics
Watanabe, Sumio (Tokyo Institute of Technology)
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.
300 pages, 13 b/w illus.
| Media | Books Hardcover Book (Book with hard spine and cover) |
| Released | August 13, 2009 |
| ISBN13 | 9780521864671 |
| Publishers | Cambridge University Press |
| Pages | 300 |
| Dimensions | 159 × 237 × 21 mm · 594 g |
| Language | English |
