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Tightness and Error Exponents of SDP with Logarithmically Many Communities

Guo, Shengtao et al.
arXiv (All) · Papers
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information-theorystatistics-theory
We study a semidefinite programming (SDP) relaxation for community recovery when the number of communities grows logarithmically. In the balanced stochastic block model with $n=km$ vertices, we consider the regime $k/\log m\toγ>0$, with edge probabilities $α\log m/m$ within communities and $β\log m/
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