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Sumio Watanabe, "Algebraic Geometry and Statistical Learning Theory"

English | 2009-09-28 | ISBN: 0521864674 | 300 pages | PDF | 1.7 mb

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.
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Tags: Learning, Theory, Statistical, Geometry, Algebraic

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