CS 688 Pattern Recognition
Home Page Fall 2016

Description: This course covers statistical pattern recognition and learning theory. Topics include Supervised Learning, Linear Models, Statistical Decision Theory Linear Methods for Regression Linear Methods for Classification Kernel Methods Model selection and assesment (other topics as time permits)

T 4:30 pm - 7:10 pm, Art and Design Building L008

Textbooks:

Pattern Recognition and Machine Learning by Bishop

A first course in Machine Learning by Rogers and Girolami 2nd Edition


Grading:

Exams: (Midterm 10/18, in class; final 12/13) 60%

Assignments: 40%


Office hours: By appointment

Announcements: