University of Illinois Urbana-Champaign 4 credits Computer Science
Basic and advanced concepts in the design and analysis of randomized algorithms. Sampling; concentration inequalities such as Chernoff-Hoeffding bounds; probabilistic method; random walks, dimension reduction; entropy; martingales and Azuma's inequality; derandomization. Randomized algorithms for sorting and searching; graphs; geometric problems. Basics of pseudorandomness and randomized complexity classes. Prerequisite: One of CS 473, CSE 414, or MATH 473; one of MATH 461, MATH 463 or STAT 400.
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