Instructor: Peter Spirtes

Office: 135D BH

Telephone: x88460

Office Hours: M,W 11:00 - 12:00

Texts: An Introduction to Bayesian Networks by F. Jensen

Spirtes, Glymour, and Scheines - Causation, Prediction and Search
Virtual Laboratory in Probability and Statistics

various articles handed out in class

Grades:

20% Quizzes

80% Homework Assignments

Assignments

1. Introduction - The problem of uncertainty - Jensen, 2.1

2. Approaches to Handling Uncertainty - Jensen, 1

3. Probability and Statistics - Jensen, 2.3.1 - 2.3.5, Probability,Virtual Laboratory, Basic Probability, Probability Spaces, 1-6.

4. Probability and Statistics - Jensen, 2.3.1 - 2.3.5, Probability,Virtual Laboratory, Basic Probability, Probability Spaces, 1-6.

5. Probability and Statistics - Jensen, 2.3.1 - 2.3.5, Probability,Virtual Laboratory, Distributions, 1-6.

6. Probability and Statistics - Jensen, 2.3.1 - 2.3.5, Probability,Virtual Laboratory, Expected Value, 1-6.

7. Interpretations of probability

Glymour - What is Probability?
Glymour - What is Probability? Continued

8. Interpretations of probability

9. Interpretations of probability

10. Conditional Independence

11. Directed Graphs - Jensen, 2.3.6 - end of chapter 2

12. Causality and Probability - SGS, pp. 41-70

13. Manipulating and Predicting - SGS, pp. 201-221

14. Parameter Estimation and Sampling Distributions - handout

15. Parameter Estimation and Sampling Distributions - handout

16. Constructing Bayes Networks - Jensen, Chapter 3

17. Constructing Bayes Networks - Bayesian approach

Heckerman - Tutorial on Learning with Bayesian Networks

18. Constructing Bayes Networks - Constraint Based Approach, SGS, pp. 101-124

19. Applications - handout

20. Updating - Jensen, chapter 4.6

21. Other Approaches - Regression, handout

22. Other Approaches - handouts

23. Other Approaches - handouts

24. Hidden Variables - handout

25. Decision Theory - Jensen, chapter 6

26. Decision Theory - Jensen, chapter 6

Homework Assignment, April 19, 1999