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Spectral Detection in the Censored Block Model

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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Preprints, Working Papers, ...
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Contributor : Emmanuelle De Laborderie Connect in order to contact the contributor
Submitted on : Thursday, April 9, 2015 - 12:04:40 PM
Last modification on : Thursday, March 17, 2022 - 10:08:44 AM

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  • HAL Id : cea-01140716, version 1
  • ARXIV : 1502.00163


Alaa Saade, Florent Krzakala, Marc Lelarge, Lenka Zdeborová. Spectral Detection in the Censored Block Model. 2015. ⟨cea-01140716⟩



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