Description: This course explores advances in algorithm design, algorithm analysis and data structures. The primary focus is on randomized and approximation algorithms, randomized and advanced data structures, and algorithmic complexity. Topics include combinatorial algorithms for cut, packing, and covering problems, linear programming algorithms, approximation schemes, hardness of approximation, random search trees, and hashing.

Format: Tutorial. Evaluation is based on weekly problem sets, several small programming projects, weekly paper summaries, and a small, final project.

Fulfills the Quantitative Reasoning requirement

Prerequisites: Computer Science 256. Computer Science 361 Recommended.

Scheduled Offerings:

	Spring 09	356T-01	(TUT)	TBA	TBA	Heeringa