18.416[J] Randomized Algorithms

Class Info

Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.

This class has 6.854J, 6.041, and 6.042J as prerequisites.

18.416[J] will not be offered this semester. It will be instructed by D. R. Karger.

This class counts for a total of 12 credits. This is a graduate-level class.

In the Spring 2015 Subject Evaluations, 18.416[J] was rated 6.5 out of 7.0. You can find more information on MIT OpenCourseWare at the Randomized Algorithms site.

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