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Algebraic Geometry and Statistical Learning Theory

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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 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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Algebraic Geometry and Statistical Learning Theory, Sumio Watanabe

Język
Rok wydania
2008
Oprawa
(twarda)
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4,5
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7 Ocena

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Tytuł
Algebraic Geometry and Statistical Learning Theory
Język
angielski
Rok wydania
2008
Oprawa
twarda
Liczba stron
300
ISBN10
0521864674
ISBN13
9780521864671
Ocena
4,45 z 5
Opis
Sure to be influential, Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are 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.