CSC310F Fall 2006 - Info

*** LECTURES MW10 (location BA024), TUTORIAL F10 (location BA024) ***

Course info sheets (ps)(pdf)

Instructor: Sam Roweis; email csc310 at cs dot toronto dot edu
Tutors: Darius Braziunas and Periklis Papakonstantinou; email csc310 at cs dot toronto dot edu

Please do NOT send Roweis or the tutor email about the class directly to their personal accounts.
They are not able to answer class email except to csc310 at cs dot toronto dot edu.

Lecture Times: Mondays, Wednesdays 10:10am -- 11:00 am
Lecture Location: Bahen 024 (basement)
First lecture Sept11, last lecture December 1
. No lecture Oct9 (Thanksgiving).

Tutorial Times: Fridays, 10:10am-11:00am
Tutorial Location: Bahen 024 (basement)
First tutorial September 22, last tutorial December 4.

Office Hours: Wednesdays 9am-10am (before class)

Prerequisite: CSC148H1/CSC150H1/CSC260H1; STA247H1/STA255H1/STA257H1/STA107H1; MAT135Y1/MAT137Y1, MAT223H1/MAT240H1
Load: 26L, 13T

Textbook
The textbook for the class will be David Mackay's book, Information Theory, Inference and Learning Algorithms.
The book is freely available online at this website.

Marking Scheme
2 small assignments worth 8% each
2 larger assignments worth 17% each
1 midterm test worth 25%
1 final test worth 25%
NO FINAL EXAM

Course Description

Measuring information. The source coding theorem. Data compression using ad hoc methods and dictionary-based methods. Probabilistic source models, and their use via Huffman and arithmetic coding. Noisy channels and the channel coding theorem. Error correcting codes, and their decoding by algebraic and probabilistic methods.

CSC310F - Information Theory || www.cs.toronto.edu/~roweis/csc310/