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Algebraic Geometry and Statistical Learning Theory - Hardcover

Algebraic Geometry and Statistical Learning Theory - Hardcover

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by Sumio Watanabe (Author)

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.

Number of Pages: 300
Dimensions: 0.8 x 9 x 6 IN
Illustrated: Yes
Publication Date: August 13, 2009
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