Nonfiction | Computer & Technology

Algebraic Geometry and Statistical Learning Theory

by Sumio Watanabe

2020-07-23 19:38:56

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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 singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-f... Read more
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. Less

Book Details

File size9x6x0.8inches
Print pages286
PublisherCambridge University Press
Publication date August 1, 2009
ISBN9780521864671
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Sumio Watanabe
Author
...

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