CSC412S/2506S Spring 2004 - Textbook and Other Readings
The textbook for the class is Michael Jordan,
An Introduction to Probabilistic Graphical Models
This textbook is not yet published, but drafts are available online.
Click here to access the book.
The user name and password will be provided in class.
Readings (tentative list, watch for updates)
- Jan5/7 - This article, plus
Sections 2.0-2.1, and 5.0-5.2 of the book.
- Jan 9 -- Probability and statistics review
notes and Chapter 13.
- Jan12/14 - rest of Chapters 2 and 5, Chapter 8
- Jan19 - Chapter 9.0-9.2, Chapter 6 except 6.2,6.4, review Chapter 8
- Jan21 - Chapter 7
- Jan26 - no book chapter, see extra notes
- Jan28 - rest of Chapter 9, Chapter 10 except EM algorithm
- Feb2/4 - rest of Chapter 10, Chapter 11
- Feb 9 - Chapter14
- Feb 11 - Chapter 9.3-9.5
- Feb 11 -- Chapter 4.2 (Factor Graphs)
- Feb23 - Bayesian model stuff and plates (review parts of Chapter 5)
- Feb25 - Chapter 3
- March1 -- Chapter 4 except message passing on factor graphs
- March 3 -- first part of Chapter 17
- March8,10 -- Chapter 12
- March15,17 -- rest of Chapter 17
- March19 -- Chapter 18 (HMM part)
- March24 -- Chapter 19
- March29 -- Chapter 20
Course Information |
Lecture Schedule/Notes |
CSC412/2506 - Uncertainty and Learning in Artificial Intelligence || www.cs.toronto.edu/~roweis/csc412/