P3.1-Nonlinear Models and Cover's Theorem

P5.1-Bayesian Learning Introductory Remarks

P3.4-Examples of Kernels

P5.4-Bayesian Regression-Simulation Examples

P1.1 - Introduction I

P3.7-Support Vector Regression

P5.7-The EM and the Linear Regression Task

P1.4-Classification

P3.10-SVM- The Hinge Loss Function