Establishes statistical and computational optimality thresholds for common subspace estimation and inference under varying SNR regimes, including an impossibility result for adaptive confidence intervals below strong inference SNR.
Levina , Elizaveta E
3 Pith papers cite this work. Polarity classification is still indexing.
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Two methods achieve vanishing misclassification for community detection in directed mean-field binary graphical models when T ≫ N (near-optimal), and exact recovery when T ≫ N², without knowing edge probability p.
Semi-relaxed Gromov-Wasserstein framework for unlabeled network learning achieves O(1/n) gap to deterministic assignments plus consistency and minimax rates for SBM and graphons.
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Community detection for binary graphical models in high dimension
Two methods achieve vanishing misclassification for community detection in directed mean-field binary graphical models when T ≫ N (near-optimal), and exact recovery when T ≫ N², without knowing edge probability p.