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7+ YearsPublisher | Cambridge University Press |
ISBN 13 | 9780521864671 |
ISBN 10 | 0521864674 |
Book Description | 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. 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. |
Language | English |
Author | Sumio Watanabe |
Publication Date | 2009 |
Cambridge Monographs on Applied and Computational Mathematic Hardcover English by Sumio Watanabe - 2009