CS 480 Randomized Algorithms and Probabilistic Analysis

Probabilistic tools used in the design and analysis of modern algorithms and data structures. Topics include: review discrete random, occupancy problems, tail bounds, Markov chains, the probabilistic method, martingales, Monte Carlo methods. The course explores a variety of CS applications. Also offered for graduate-level credit as CS 580 and may be taken only once for credit.