6.842 Randomness and Computation
The power and sources of randomness in computation. Connections and applications to computational complexity, computational learning theory, cryptography and combinatorics. Topics include: probabilistic proofs, uniform generation and approximate counting, Fourier analysis of Boolean functions, computational learning theory, expander graphs, pseudorandom generators, derandomization.
This class counts for a total of 12 credits. This is a graduate-level class.
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© Copyright 2015 Yasyf Mohamedali