Low-degree evidence for computational transition of recovery rate in stochastic block model
–Neural Information Processing Systems
We investigate implications of the (extended) low-degree conjecture (recently formalized in [moitra et al2023]) in the context of the symmetric stochastic block model. Assuming the conjecture holds, we establish that no polynomial-time algorithm can weakly recover community labels below the Kesten-Stigum (KS) threshold. In particular, we rule out polynomial-time estimators that, with constant probability, achieve $n^{-0.49}$
Neural Information Processing Systems
Jun-13-2026, 17:25:28 GMT
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