Appendix 2: Introduction to Statistical learning
Jedediah Singer and Gabriel Kreiman
Children's Hospital Harvard Medical School and Swartz Center for Theoretical Neuroscience, Harvard University

This is a brief introduction to the field of statistical learning with multiple references to the mathematical literature. We discuss the setting of the learning problem, how supervised learning problems can be formulated and addressed and several algorithms to learn from data including Fisher linear discriminant, nearest neighbors, support vector machines. The discussion is linked to a neurophysiological recordings from ensembles of neurons.

Key words: statistial learning, artificial intelligence, fisher classifier, support vector machines, supervised learning