9780521864671-0521864674-Algebraic Geometry and Statistical Learning Theory (Cambridge Monographs on Applied and Computational Mathematics, Series Number 25)

Algebraic Geometry and Statistical Learning Theory (Cambridge Monographs on Applied and Computational Mathematics, Series Number 25)

ISBN-13: 9780521864671
ISBN-10: 0521864674
Edition: 1
Author: Sumio Watanabe
Publication date: 2009
Publisher: Cambridge University Press
Format: Hardcover 300 pages
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Book details

ISBN-13: 9780521864671
ISBN-10: 0521864674
Edition: 1
Author: Sumio Watanabe
Publication date: 2009
Publisher: Cambridge University Press
Format: Hardcover 300 pages

Summary

Algebraic Geometry and Statistical Learning Theory (Cambridge Monographs on Applied and Computational Mathematics, Series Number 25) (ISBN-13: 9780521864671 and ISBN-10: 0521864674), written by authors Sumio Watanabe, was published by Cambridge University Press in 2009. With an overall rating of 3.6 stars, it's a notable title among other AI & Machine Learning (Computer Science) books. You can easily purchase or rent Algebraic Geometry and Statistical Learning Theory (Cambridge Monographs on Applied and Computational Mathematics, Series Number 25) (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $17.08.

Description

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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