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Spectral Detection in the Censored Block Model

31 January 2015
Alaa Saade
Florent Krzakala
Marc Lelarge
Lenka Zdeborová
ArXiv (abs)PDFHTML
Abstract

We consider the problem of partially recovering hidden binary variables from the observation of (few) censored edge weights, a problem with applications in community detection, correlation clustering and synchronization. We describe two spectral algorithms for this task based on the non-cktracking and the Bethe Hessian operators. These algorithms are shown to be asymptotically optimal for the partial recovery problem, in that they detect the hidden assignment as soon as it is information theoretically possible to do so.

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