CSCE 582 Spring 2009 Syllabus

CSCE 582 Spring 2009: Syllabus

The textbook is:

Jensen, Finn V. Bayesian Networks and Decision Graphs. New York: Springer-Verlag, 2007 (ISBN-10 0-387-68281-3; ISBN-13: 978-0-387-68281-5) (Approximately $64 at amazon.com. This text is referred to as [J07].) Other recommended books on the topic are:

Uffe B. Kjaerulff and Anders L. Madsen. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis. New York: Springer-Verlag, 2008 (ISBN 978-0-387-74100-0).
Kevin B. Korb and Ann E. Nicholson. Bayesian Artificial Intelligence. London: Chapman & Hall and CRC Press, 2004 (ISBN 1-58488-387-1).
Jensen, Finn V. Bayesian Networks and Decision Graphs. New York: Springer-Verlag, 2001 (ISBN 0-387-95259). (This text is referred to as [J01].)
Robert G. Cowell, A. Philip Dawid. Steffen L. Lauritzen, and David J. Spiegelhalter. Probabilistic Networks and Expert Systems. New York: Springer, 1999 (ISBN 0-387-98767-3).
Jensen, Finn V. An Introduction to Bayesian Networks. New York: Springer-Verlag, 1996 (ISBN 0-387-91502-8). (This text is referred to as [J96].)
Richard E. Neapolitan. Probabilistic Reasoning in Expert Systems: Theory and Algorithms. New York: Wiley, 1990 (ISBN 0-471-61840-3).
Judea Pearl. Probabilistic Reasoning in Intelligent Systems. San Francisco: Morgan-Kaufmann, 1988 (ISBN 0-934613-73-7).

The last day to withdraw without failure is Monday, February 23, 2009. The final exam for the course will take place on Monday, May 4, 2009, at 9am in the classroom (SWGR 2A21). This is the regularly scheduled time for courses taught from 1:25pm to 2:15pm on Tuesdays and Thursdays. The syllabus is tentative.

Week Begins	Lecture Topics	Readings
1: January 12, 14, 16	Probability and Reasoning	Ch.1 [J07]; instructor's slides
2: January 21, 23	Causal and Bayesian Neworks	Ch.2 [J07]
3: January 26, 28, 30	Building Models: Capturing the Structure and Determining the Conditional Probabilities	Sections 3.1 and 3.2 [J07]
4: February 2, 4, 6	Building Models: Advanced Modeling Methods and Special Features	Sections 3.3 and 3.4 [J07]
5: February 9, 11, 13	Belief Updating in Bayesian Networks: Structure Based Algorithms	Sections 4.1-4.6 [J07]
6: February 16, 18, 20	Belief Updating in Bayesian Networks: Space-Time Tradeoff and Iterative Methods; Test	Sections 4.7-4.9 [J07] and Test
7: February 23, 25, 27	Graphical Languages for Decision Problems	Ch.9 [J07]
8: March 2, 4, 6	Analysis Tools for Bayesian Networks	Ch.5 [J07]
9: March 16, 18, 20	Methods for Analyzing Decision Problems	Ch.11 [J07]
10: March 23, 25, 27	Parameter Estimation	Ch.6 [J07]
11: March 30, April 1, 3	Basics of Structure Learning	Ch.7 [J07]
12: April 6,8,10	TBD	TBD
13: April 13, 15, 17	TBD	TBD
14: April 20, 22, 24	TBD	TBD
15: April 27, 29; May 1, 4	TBD	TBD