Courses:

Statistical Learning Theory and Applications >> Content Detail

Calendar / Schedule

Calendar

There are three sessions, two Math Camps and an extra topic, at the bottom of the calendar. These will be given when students require the background needed to understand the next series of lectures and problems.


	LEC #				TOPICS


	1				The Course at a Glance


	2				The Learning Problem in Perspective


	3				Regularization and Reproducing Kernel Hilbert Spaces


	4				Regression and Least-Squares Classification


	5				Support Vector Machines for Classification


	6				Generalization Bounds, Intro to Stability


	7				Stability of Tikhonov Regularization


	8				Consistency and Uniform Convergence over Function Classes


	9				Necessary and Sufficient Conditions for Uniform Convergence


	10				Bagging and Boosting


	11				Computer Vision, Object Detection


	12				Loose Ends


	13				Approximation Theory


	14				RKHS, Mercer Thm, Unbounded Domains, Frames and Wavelets


	15				Bioinformatics


	16				Text


	17				Regularization Networks


	18				Morphable Models for Video


	19				Leave-One-Out Approximations


	20				Bayesian Interpretations


	21				Multiclass Classification


	22				Stability and Glivenko-Cantelli Classes


	23				Symmetrization, Rademacher Averages


	24				Project Presentations


	25				Project Presentations


	Math Camp				Lagrange Multipliers/Convex Optimization


	Math Camp				Functional Analysis


	Extra Topic				SVM Rules of Thumb

Course Home

Courses:

Statistical Learning Theory and Applications >> Content Detail

Table of Contents

Calendar / Schedule