CSC 523

Randomized Algorithms

Units: 1.5

Basic techniques in design and analysis of randomized algorithms: moments and deviations, Markov chains and random walks, martingales, and algebraic techniques. Other topics include: the probabilistic method, random structures and complexity. Applications are selected from: parallel algorithm, routing networks, combinatorial optimization, data structure, approximate solutions to intractable problems, cryptography, pattern matching, and computational geometry.

Graduate course in the Computer Science program offered by the Faculty of Graduate Studies.

Summer 2019 Fall 2019 Spring 2020

Summer timetable available: February 15. Fall and Spring timetables available: May 15.

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