G22.3033-006, Special Topics in Information Theory,
Davi Geiger,
Graduate Division, Computer Science


 

Classes: Thursday.
Class Room: WWH
Instructor
Davi Geiger, geiger@cs.nyu.edu
Office: 715 Broadway, 714.
Phone: +1 (212) 998-3235
Office Hours: Thursday 3:30pm-5pm.

Course Description

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.

Evaluation Process

There will be homeworks, about every three weeks, basically from the book.
There will be a final exam.

Book

Elements of Information Theory.
Thomas M. Cover and Joy A. Thomas .
Publisher: Wiley-Interscience Publication.

Syllabus

Class 1: Introduction

Class 2:

Class 3:

Class 4:

Class 5:

Class 6:

Class 7:

Class 8:.

Class 9:

Under construction. Please see instructor for more details regarding this course