 
 

1  10/19  Introduction to Probability  

2  10/26  Probability Theory and Bayes Theorem  
3  11/02  Random Variable and Probability Distribution  
4  11/09  Multivariate Probability Distribution  
5  11/16  Maximum Likelihood  
6  11/30  Mixture Models  
7  12/07  Model Selection  
8  12/14  Hidden Markov Model (1)  
9  12/21  Hidden Markov Model (2)  
10  01/11  Graphical Models (1)  
11  01/18  Graphical Models (2)  
12  01/25  Bayesian Network  
13  02/01  Sampling and Simulation  
02/08  ***Cancel***  
14  02/15  Summary 
1  01/11  Duy Le  An adaptive colorbased particle filter, Image Vision Computing, 2003  

2  01/18  Masoomeh Torabzadeh  On the SelfSimilar Nature of Ethernet Traffic, IEEE/ACM Trans. Networking, 1994  
3  01/25  Sano Masanori  An Integrated Baseball Digest System Using Maximum Entropy Method, ACM Multimedia 2002  
4  02/01  Nguyen Phuoc Tat Dat  Tagging English Text with a Probabilistic Model, 1994  
5  02/15  Nguyen Luu Thuy Ngan  Probabilistic Reasoning for Entity & Relation Recognition, COLING'02 
