New techniques establish sharp lower bounds ruling out low-degree polynomial estimation at the BBP and Kesten-Stigum thresholds for planted submatrix, dense subgraph, spiked Wigner, and stochastic block models.
Testing network correlation efficiently via counting trees
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Proves node subsampling asymptotically approximates joint distribution of network moments under sparse graphon, enabling two-sample tests for unmatchable networks with unequal densities.
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Sharp Phase Transitions in Estimation with Low-Degree Polynomials
New techniques establish sharp lower bounds ruling out low-degree polynomial estimation at the BBP and Kesten-Stigum thresholds for planted submatrix, dense subgraph, spiked Wigner, and stochastic block models.
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Multivariate Inference of Network Moments by Subsampling
Proves node subsampling asymptotically approximates joint distribution of network moments under sparse graphon, enabling two-sample tests for unmatchable networks with unequal densities.