Local Statistics, Semidefinite Programming, and Community Detection
berkeley.edu
Local Statistics, Semidefinite Programming, and Community Detection
We propose a new semidefinite programing hierarchy for statistical inference problems and illustrate its efficacy on the problem of community detection in block models, a model of random graphs where vertices are partitioned into $k$ communities, and a graph is sampled conditional on a prescribed number of inter- and intra-community edges. The ...
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Semidefinite Programming Applications
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