Fall 2011 Course Descriptions
COMP 136-01 Statistical Pattern Recognition
TR 10:30-11:45, Halligan Hall 106
D+ Block
Statistical foundations and algorithms for machine learning with a focus on Bayesian modeling. Topics include: classification and regression problems, regularization, model selection, kernel methods, support vector machines, Gaussian processes, Graphical models.
Prerequisite: Prerequisites: MATH 13; MATH 46; EE 104 or MATH 162; COMP 40 or COMP 80 or a programming course using Matlab. COMP 135, or COMP 131 are recommended but not required. Or permission of instructor.