The Expander Mixing Lemma states that edges in a d-regular graph are evenly distributed throughout the graph, and the number of edges between two vertex subsets is close to what would be expected in a random d-regular graph.
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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