CSCE 582 Spring 2016 Syllabus

CSCE 582 Spring 2016: 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 12, 2014. The last day to drop the course without a grade of "W" being recorded is Tuesday, January 19, 2016. The last day to withdraw without failure is Thursday, March 3, 2016. The last day of classes is Thursday, April 21, 2016. The final exam for the course is Tuesday, May 3, 2016, at 1230 in the classroom (300 Main B111). This is the regularly scheduled time for courses taught from 1315 to 1430 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 exam is only tentative.

Week	Lecture Topics	Readings
1: January 12 and 14	Probability and Reasoning	Chs.1 and 2 [J07]; instructor's slides
2: January 19 and 21	Probability and Reasoning;	Chs.1 and 2 [J07]; instructor's slides
3: January 26 and 28	Causal and Bayesian Networks	Ch.2 [J07]
4: February 2 and 4	Causal and Bayesian Networks	Ch.2 [J07]
5: February 9 and 11	Building Models: Capturing the Structure and Determining the Conditional Probabilities	Sections 3.1 and 3.2 [J07]
6: February 16 and 18	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 23 and 25	Midterm and Building Models: Advanced Modeling Methods and Special Features	Sections 3.3 and 3.4 [J07]
8: March 1 and 3	Building Models: Advanced Modeling Methods and Special Features	Sections 3.3 and 3.4 [J07]
9: March 8 and 10	Spring Break	TBA
10: March 15 and 17	Belief Updating in Bayesian Networks: the Junction Tree Method	Ch.4 [J96]
11: March 22, 24	Belief Updating in Bayesian Networks: The Junction Tree Method	Ch.4 [J96]
12: March 29 and 31	Belief Updating in Bayesian Networks: Stochastic Simulation and Loopy Belief Propagation	Sections 4.7-4.8 [J07] and Notes
13: April 5 and 7	Graphical Languages for Decision Problems	Ch.9 [J07]
14: April 12 and 14	Graphical Languages for Decision Problems	Ch.9 [J07]
15: April 19 and 21	Graduate and Honors Student Presentations	TBA