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
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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.
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Statistically and Computationally Optimal Estimation and Inference of Common Subspaces
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.