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Applications of Markov Chains to Combinatorics

Student-Run Discrete Math Seminar

Speaker: David Sivakoff, UC Davis
Location: 2112 MSB
Start time: Thu, Jan 31 2008, 3:10PM

Suppose S is a large set of combinatorial structures, and \pi is a probability distribution on S. The ability to sample efficiently from S according to \pi can lead to polynomial time approximate solutions to computationally hard problems. Without getting into too much detail, I will discuss examples of how Markov Chains can be used to sample approximately uniformly from S, and how such sampling can be used to estimate |S|. Examples may include the Knapsack Problem and card shuffling.