8803 Connections between Learning, Game Theory, and Optimization, Fall 2010

Course Information

Lectures:  Tues/Thurs 4:35-5:55, Instr Center 117.

Instructor: Maria Florina Balcan (KACB 2144 , 404-385-8640).

Course Description: Over the past 10 years, researchers have discovered a number of important and deep connections between machine learning theory, algorithmic game theory, and combinatorial optimization. This course will explore these connections, discussing fundamental topics in each area and how ideas from each area can shed light on the others.

Prerequisites: No specific background in learning theory or game theory is required.

Evaluation and Responsibilities: Grading will be based on 4 homework assignments and a class presentation or project.

General structure of the course: Here is a short outline of the "core" portion (some bullets correspond to multiple lectures):

Textbooks: The recommended (not required) textbook is Algorithmic Game Theory by Noam Nisan, Tim Rougharden, Eva Tardos, and Vijay Vazirani. You can find a link to free online edition here. Additionally, we will use a number of papers, survery articles, and tutorials.