CSCE 582 Spring 2014 Syllabus

CSCE 582 Spring 2014: Syllabus

The textbook is:

Jensen, Finn V. and Thomas D. Nielsen. Bayesian Networks and Decision Graphs. New York: Springer-Verlag, 2007 (ISBN-10 0-387-68281-3; ISBN-13: 978-0-387-68281-5) (Approximately $70 at amazon.com. This text is referred to as [J07].) Other recommended books on the topic are:

Adnan Darwiche. Modeling and Reasoning with Bayesian Networks Cambridge, UK: Cambridge University Press, 2009 (ISBN 978-0-521-88438-9).
Daphne Koller and Nir Friedman. Probabilistic Graphical Models: Principles and Techniques. Cambridge, MA: The MIT Press, 2009 (ISBN 978-0-262-0139-2).
Timo Koski adn John M. Noble. Bayesian Networks: An Introduction. Chichester, UK: Wiley, 2009 (ISBN 978-0-470-74304-1).
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, 2nd ed. London: Chapman & Hall and CRC Press, 2011 (ISBN 978-1-4398-1591-5). (First edition: 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 main (approximately 80% of the time) instructional delivery strategy for this course is lectures. Discussions based on student presentations, videos, quizzes or in-class exercises, and a possible invited talk will make up the remaining 20% of time. The first day of classes is Tuesday, January 14, 2014. The last day to withdraw without failure is Monday, March 3, 2014. The last day of classes is Thursday, April 24, 2012. The final exam for the course is Saturday, May 3, 2014, at 1230 in the classroom (SWGR 2A22). This is the regularly scheduled time for courses taught from 1450 to 1605 on Tuesdays and Thursdays. (See the university exam schedule.) The syllabus is tentative. It is especially important for students to be aware that the date of the midterm test or tests is only tentative.

Week	Lecture Topics	Readings
1: January 14 and 16	Probability and Reasoning	Chs.1 and 2 [J07]; instructor's slides
2: January 21 and 23	Probability and Reasoning;	Chs.1 and 2 [J07]; instructor's slides
3: January 28 and 30	Causal and Bayesian Networks	Ch.2 [J07]
4: February 4 and February 6	Causal and Bayesian Networks	Ch.2 [J07]
5: February 11 and 13	Building Models: Capturing the Structure and Determining the Conditional Probabilities	Sections 3.1 and 3.2 [J07]
6: February 18 and 20	Building Models: Capturing the Structure and Determining the Conditional Probabilities	Sections 3.2 and 3.3 [J07] and Notes on the Stratum Method
7: February 25 and 27	Midterm and Building Models: Advanced Modeling Methods and Special Features	Sections 3.3 and 3.4 [J07]
8: March 4 and 6	Building Models: Advanced Modeling Methods and Special Features	Sections 3.3 and 3.4 [J07]
9: March 11 and 13	Spring Break	TBA
10: March 18 and 20	Belief Updating in Bayesian Networks: the Junction Tree Method	Ch.4 [J96]
11: March 25, 27	Belief Updating in Bayesian Networks: The Junction Tree Method	Ch.4 [J96]
12: April 1 and 3	Belief Updating in Bayesian Networks: Stochastic Simulation and Loopy Belief Propagation	Sections 4.7-4.8 [J07] and Notes
13: April 8 and 10	Graphical Languages for Decision Problems	Ch.9 [J07]
14: April 15 and 17	Graphical Languages for Decision Problems	Ch.9 [J07]
15: April 22 and 24	Graduate and Honors Student Presentations	TBA