Algebraic Geometry and Statistical Learning Theory - Sumio Watanabe
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Sure to be influential, Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
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Description
More Information
| Author | Sumio Watanabe |
|---|---|
| Publisher | Cambridge University Press |
| Release year | 2017 |
| Cover type | Hardcover |
| EAN | 9780521864671 |