Prof. Dmitry Panchenko
MIT Course Number
As Taught In
The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory.
Other OCW VersionsThis is a graduate-level subject in Statistics. The content varies year to year, according to the interests of the instructor and the students.