15-859(M): Randomized Algorithms, Spring 2011 course description

Avrim Blum and Anupam Gupta
Time: MW 1:30-2:50, GHC 4102
Course blog: http://cmurandomized.wordpress.com/

Office Hours: TBA

Course description:

Randomness has proven itself to be a useful resource for developing provably efficient algorithms and protocols. As a result, the study of randomized algorithms has become a major research topic in recent years. This course will explore techniques for effectively using randomization and for analyzing randomized algorithms, as well as examples from a variety of settings and problem areas.

Prerequisites: Mathematical maturity; exposure to undergraduate material in Algorithms, and in Discrete Probability and Combinatorics. If you are not sure whether your background suffices, please see us.

Method of Evaluation: Grading will be based on (approximately bi-weekly) homework assignments, class participation and a take-home final. As part of class participation, each student (possibly in teams) will do a short project/presentation on a topic chosen in consultation with the instructors.

Textbook: Randomized Algorithms, Motwani and Raghavan. Other very nice books in the area include:

Material will be supplemented by handouts and papers.

Topics: A tentative list of topics includes: