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Algebraic Geometry and Statistical Learning Theory

By: Sumio (Tokyo Institute of Technology) Watanabe (Author)

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Ksh 17,500.00

Format: Hardback or Cased Book

ISBN-13: 9780521864671

Publisher: Cambridge University Press

Publication Date: Aug 13th, 2009

Weight: 590 grams

Dimension: 23.70 x 15.90 x 2.10 cms

Category: Algebraic geometry

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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.

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