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.
6.842 will be offered this semester (Fall 2017). It is instructed by R. Rubinfeld.
Lecture occurs 11:00 AM to 12:30 PM on Mondays and Wednesdays in 4-261.
This class counts for a total of 12 credits.
© Copyright 2015 Yasyf Mohamedali