G22.3033-006, Special Topics in Information Theory,
Graduate Division, Computer Science
Class Room: WWH Instructor
Davi Geiger, email@example.com
Office: 715 Broadway, 714.
Phone: +1 (212) 998-3235
Office Hours: Thursday 3:30pm-5pm.
This course will look at basic ideas on Information Theory and some
effort will be devoted to how they work when applied to computer vision
and speech. Students will be encouraged to understand well the
material via homeworks. The course will cover basic Information Theory
including Entropy, Relative Entropy, Mutual Information, Entropy Rates
of Stochastic Processes, Data Compression, Kolmogorov Complexity,
Channel Capacity, Differential Entropy, Statistics, Law of Large
Numbers, Large Deviation Theory.
There will be homeworks, about every three weeks, basically from the book.
There will be a final exam.
Elements of Information Theory.
Thomas M. Cover and Joy A. Thomas .
Publisher: Wiley-Interscience Publication.
Class 1: Introduction
Please see instructor for more details regarding this