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Cambridge University Press, Algebraic Geometry and Statistical Learning Theory The Cambridge Monographs on Applied and Computational Mathematics reflect the crucial role of mathematical and computational techniques in contemporary science. Algebraic geometry and singularity theory provide the mathematical foundation on which a new In this talk, we give a basic introduction to Sumio Watanabe's Singular Learning Theory, as outlined in his book "Algebraic Geometry and Statistical Learning Theory". Watanabe's key insight to studying singular models was to use a deep result in algebraic geometry known as Hironaka's Resolution of Singularities.

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2020-10-27 · Algebraic geometry and number theory The group conducts research in a diverse selection of topics in algebraic geometry and number theory. Areas of interest and activity include, but are not limited to: Clifford algebras, Arakelov geometry, additive number theory, combinatorial number theory, automorphic forms, L-functions, singularities, rational points on varieties, and algebraic surfaces.

Q325.7.W38 2009 006.3 1 – dc22 2009011366 ISBN 978-0-521-86467-1 hardback Algebraic Geometry and Statistical Learning Theory 1st Edition by Sumio Watanabe and Publisher Cambridge University Press. Save up to 80% by choosing the eTextbook option for ISBN: 9781107713963, 110771396X. The print version of this textbook is ISBN: 9780521864671, 0521864674. Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory.Many widely used statistical models are singular: mixture models, neural networks, HMMs, and Bayesian networks are major examples.