Computer Science and Engineering

CSE 269 Approximation Algorithms

Meant for graduate students with a good mathematical background. Students should be familiar with discrete math, algorithms, calculus/probability, graph theory. Topics include clustering, linear programming, LP duality, semidefinite programming, etc.

Requirements

Enrollment is restricted to graduate students or by permission of the instructor. Students taking this course need to have had at least one prior course in algorithms, similar to CSE 102 or equivalent. Students need a solid background in analysis of algorithms, discrete math, probability theory, graph theory, and overall mathematical maturity.

Credits

5

Quarter offered

Fall

Instructor

Evangelos Chatziafratis