CS790: Information Theory, Machine Learning and Statistics
Fall 2007


Information
Syllabus
Selected Readings

Syllabus (Subject to revision as the quarter progresses)

Day Topic Reading Optional Reading
9/04/07 Entropy, mutual information CT 2.1-2.2 Information Theory at WikiPedia
9/06/07 Relative entropy, Bregman distance CT 2.3-2.5 Relative Entropy at WikiPedia; Bregman Distance at WikiPedia
9/11/07 Jensen's inequality and its applications CT 2.6-2.7
9/14/07 Fano's Inequality CT 2.10
9/18/07 Entropy rate CT 4.1-4.4, 7.6
9/20/07 Entropy rate of HMM CT 4.5
9/25/07 Asymptotic equipartition property CT 3
9/27/07 Data compression CT 5
10/02/07 Gambling and data compression CT 6
10/04/07 On the method of types CT 10.1
10/09/07 Lossy source coding and the rate distortion function CT 10.1-10.4
10/11/07 Rate distortion theorem CT 10.4-10.8
10/16/07 Channel coding and capacity CT 7.1-15.3
10/18/07 Channel capacity theorem CT 15.4-15.7
10/23/07 Joint source channel coding CT 7.13
10/25/07 Duality: maximum entropy and maximum likelihood estimation for Markov random fields CT 12 Maximum Entropy at Adam Berger's Site; Maximum Entropy at WikiPedia; Markov Random Fields at WikiPedia;
10/30/07 Maximum entropy, boosting, information geometry and alternating algorithms CT 12 Information Geometry at WikiPedia
11/01/07 Universal source coding and online learning CT 13.1-13.2
11/06/07 Coding theory and approximate inference in graphical models DM Part VI
11/08/07 Project Presentations