Probability and AI - Syllabus, Spring 2002

80-316 and 80-616

http://www.andrew.cmu.edu/user/ps7z/syll2002.html

 


Instructor:  Peter Spirtes          

Office:  135D BH

Telephone:  x88460

Office Hours:  T,Th 12:30-1:20


e-mail: ps7z@andrew.cmu.edu

 

Texts:  An Introduction to Bayesian Networks by F. Jensen

various articles handed out in class

for graduate students: Causality by Judea Pearl

http://www.hugin.com/news/Demo_HDE.article

http://www.phil.cmu.edu/courses/csr/

 

Grades:  20% Quizzes

               60% Homework Assignments

               20% Final

 

1.      Introduction

            Lecture 1

2.      Causation

            Jensen 1.1.-1.2

http://www.phil.cmu.edu/courses/csr/ Causation Among Variables

http://www.phil.cmu.edu/courses/csr/ Indeterministic Causation

Lecture 2

3.      Causation –

http://www.phil.cmu.edu/courses/csr/ – Causation – Causal graphs

http://www.phil.cmu.edu/courses/csr/ Causation – Interventions

Lecture 3

4.      Approaches to Uncertainty

            http://developer.hugin.com/Getting_Started/ Paradigms

5.      Probability I

            Jensen, 1.3,

http://www.math.uah.edu/stat  Probability - Probability Spaces, 1 – 5

Lecture 4

6.       Probability II

           Jensen, 1.3,

           http://www.math.uah.edu/stat/  Probability - Distributions, 1 – 6

           Homework

           Answers

7.      Probability III

           Jensen, 1.3,

           http://www.math.uah.edu/stat/  Probability – Expected Values, 1 – 3, 5 – 6

8.      Probability IV – 

           http://www.math.uah.edu/stat/   Probability – Probability Spaces, 6

     Online Causal Course – Association – Independence and Association

                 Online Causal Course – Association – Conditional Independence

9.      Interpretations of probability

10.    Bayesian Networks – 

            Jensen, 1.4.

http://developer.hugin.com/Getting_Started/ Bayesian Networks

11.    Causality and Probability

http://www.phil.cmu.edu/courses/csr/ Causation to Association – Unconditional association

http://www.phil.cmu.edu/courses/csr/ Causation to Association – Conditional

            association

http://www.phil.cmu.edu/courses/csr/ Course – Causation to Association – d-

                  separation

12.    Constructing Bayesian Networks

           Jensen, 2

           http://developer.hugin.com/Getting_Started/  Tutorials – Building a Bayesian

           Network

           Homework

13.    Updating

                 Jensen, 5.7

                 handout

                 Hugin exercises

14.    Manipulating and Predicting

            http://www.phil.cmu.edu/courses/csr/ Interventions

15.    Parameter Estimation and Sampling Distributions        

            http://www.math.uah.edu/stat/ Random Samples, sections 1-6, 9

16.    Parameter Estimation and Sampling Distributions

            http://www.math.uah.edu/stat/ Point Estimation, sections 1, 3-6

            Homework

17.    Applications

            http://www.research.microsoft.com/~heckerman/default.htm

18.    Other Approaches to Classification: Regression

            handout

19.    Other Approaches to Classification

            Notes

            Homework 6

            Notes for Homework 6

20.    Causal inference

http://www.phil.cmu.edu/courses/csr/ Association to Causation – Problems

            with Causal Discovery

http://www.phil.cmu.edu/courses/csr/ Association to Causation – Confounding

21.    Constructing Bayes Networks – Bayesian methods

            http://www.research.microsoft.com/~heckerman/default.htm

22.    Constructing Bayes Networks: Constraint Based Methods

            Handout 1  for Constraint Based Methods

            Handout 2  for Constraint Based Methods

            Handout 3 for Constraint Based Methods

            Study Guide for Second Quiz

            Homework 7

23.    Latent Variable Inference I

            Handout for Latent Variables Methods

24.    Latent Variable Inference II