Algebraic Geometry and Statistical Learning Theory

Sure to be influential Watanabes 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.