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Cambridge Monographs on Applied and Computational Mathematics

Algebraic Geometry and Statistical Learning Theory (Cambridge Monographs on Applied and Computational Mathematics) by 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 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.

Hardcover

First published August 1, 2009

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