The Expander Walk Sampling Theorem states that random walks on expander graphs can be used to sample vertices from a uniform distribution. It was first proposed by Ajtai, Komlós & Szemerédi in 1987 and further developed by Gillman in 1998.
UC Berkeley
Fall 2021
This course explores the role of randomness in computation and pseudorandomness, focusing on the applications in error-correcting codes, expander graphs, randomness extractors, and pseudo-random generators. The course will also address the question of derandomization of small-space computation. Prerequisites are unspecified, but the course content suggests a high level of expertise.
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