Breaking the Multicommodity Flow Barrier for ?log(n)-Approximations to Sparsest Cut
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Microsoft Research330 тыс
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13.02.23 – 2 0041:13:57Опубликовано 17 августа 2016, 21:25
We present an algorithm for the sparsest cut problem that simultaneously achieves the better approximation factor of SDP/multicommodity-flow based algorithms and the subquadratic running time of single-commodity flow based algorithms. The idea is that we can turn Arora, Rao, and Vazirani's matching-chaining argument into an algorithm for finding good augmenting paths in a multicommodity flow network. Our analysis follows ARV's, making essential use of measure concentration on the sphere.
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