Algebraic Geometry and Statistical Learning Theory

Cambridge Monographs on Applied and Computational Mathematics

by Sumio Watanabe

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.

Genres: Mathematics, Textbooks

300 pages, Kindle Edition

First published August 1, 2009