Professor Harry Wechsler

Department of Computer Science

George Mason University

Fairfax, VA 22030

e-mail : wechsler@cs.gmu.edu

web : http://cs.gmu.edu/~wechsler/

           (703) 993-1533 (office)

(703) 993-1530 (sec)

(703)993-1710 (fax)

 

GEORGE MASON UNIVERSITY

         SPRING   '2007

 

 CS 775 --- PATTERN   RECOGNITION

 001  12181    R   7:20 p.m. –  10:00 p.m.   IN    211

(cross listed with IT  844 --- PATTERN  RECOGNITION)

 

Office Hours

R   6:15 p.m. - 7:00 p.m. or by appointment (SITE II - Rm. 461)

          Textbook

          1. C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.

References

 

1.  V. Cherkassky and F. Mulier, Learning from Data: Concepts, Theory, and Methods,  Wiley, 1999.

 

2. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines, Cambridge   University Press, 2001.

 

         3.   R. Duda, P. Hart and D. Stork, Pattern Classification, Wiley, 2002.

 

4.  S. Haykin, Neural Networks (2nd ed.), Prentice-Hall, 1999.

 

5. V. Vapnik, The Nature of Statistical Learning Theory (2nd. ed.), Springer, 2000.

 

       

Course Description

           Explores statistical  pattern recognition, neural networks, and statistical learning theory.

           Pattern recognition topics include Bayesian   classification and decision theory,

           density (parametric and non – parametric) estimation, linear and non – linear

           discriminant analysis, dimensionality reduction, feature extraction and selection,

           mixture models and expectation – maximization (EM), and vector quantization

           and clustering. Neural networks topics include feed-forward networks and  

           back-propagation, self-organization feature maps, and   radial basis functions.

           Statistical learning theory covers model selection and support vector machines (SVM).

           Course emphasizes experimental design, applications, and performance evaluation.

 

 

          Schedule

 

         1st day of classes: January 24, 2007

 

         Spring Break:  March 15, 2007

 

         Last Day of Classes: May 3, 2007

          

Grading

1. Homework Assignments: 30 %

2. Midterm: 20% < March 22, 2007>

2. TERM PROJECT:  Literature Survey (10%) and Project (40%).