CSC412S Spring 2006 - Info
*** LECTURES MW 2:10-3:00pm GB244 ***
*** TUTORIALS F 2:10pm GB244 ***
Course info sheets (ps)(pdf)
Instructor: Sam Roweis; email csc412 at cs.toronto.edu
Tutor: Ruslan Salakhutidnov; email csc412 at cs.toronto.edu
Please do NOT send Roweis or tutor email about the class
directly to their personal accounts.
They are not able to answer class email
except to cs412 at cs.toronto.edu.
Lecture Times: Mondays, Wednesdays 2:10pm -- 3:00pm
First lecture Jan 9, last lecture April 7.
No lectures Feb 20/22 (Reading Week).
Tutorial Times: Fridays, 2:10pm-3:00pm
Tutorial Location: GB244
First tutorial Jan 13, last tutorial April 10.
No tutorial Feb 24 (Reading Week).
Office Hours: Wednesdays 11-12 or by appointment
Prerequisite: CSC411H (except in 2006); CGPA 3.0;
but permission of instructor can waive these
Load: 26L, 13T
Michael Jordan, An Introduction to Probabilistic Graphical Models
This textbook is not yet published, but drafts will be provided in class.
2 small assignments worth 10% each
2 larger assignments worth 15% each
1 midterm test worth 25%
1 final test worth 25%
NO FINAL EXAM
A senior undergraduate class on graphical models
and probabilistic networks in AI.
Representing uncertain knowledge using probability and other
formalisms. Qualitative and quantitative specification of probability
distributions using graphical models. Algorithms for inference with
graphical models. Statistical approaches and algorithms for learning
models from experience. Examples will be given of applications of
these models in various areas of artificial intelligence.
Course Information |
Lecture Schedule/Notes |
CSC412 - Probabilistic Learning and Reasoning || www.cs.toronto.edu/~roweis/csc412/