The maximum cut problem is the task of finding a partition of a graph's vertices into two sets such that the number of edges between them is maximized. There is also a weighted version of the problem, where each edge has an associated weight and the objective is to maximize the total weight of the edges between the two sets. The weighted max-cut problem can be transformed into a weighted minimum cut problem by flipping the sign in all weights.
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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