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

Inhaltsangabe

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. The theory achieved here underpins accurate estimation techniques in the presence of singularities.

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