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Algebraic Geometry and Statistical Learning Theory (Hardcover)

Author: Watanabe, Sumio

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Product Overview

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.

Specifications

Publisher Cambridge Univ Pr
Mfg Part# 9780521864671
SKU 211067732
Format Hardcover
ISBN10 0521864674
Release Date 8/1/2009
Product Attributes
eBooks Kobo
Book Format Hardcover
Number of Pages 0286
Publisher Cambridge University Press
Series Part 25
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