The spectral weak-recovery threshold for linearized AMP in the multi-view spiked Wigner model is SNR(λ,B)=1, where SNR is the largest eigenvalue of Diag(√λ)(B⊙B)Diag(√λ), and this coincides with the information-theoretic threshold for a broad class of spike priors.
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A multi-stage smoothing estimator is developed to estimate time-varying network edge probabilities under Hölder smoothness and piecewise Lipschitz conditions.
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Sharp Spectral Thresholds for Multi-View Spiked Wigner Models
The spectral weak-recovery threshold for linearized AMP in the multi-view spiked Wigner model is SNR(λ,B)=1, where SNR is the largest eigenvalue of Diag(√λ)(B⊙B)Diag(√λ), and this coincides with the information-theoretic threshold for a broad class of spike priors.
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Nonparametric estimation of time-varying network connections by multi-stage smoothing
A multi-stage smoothing estimator is developed to estimate time-varying network edge probabilities under Hölder smoothness and piecewise Lipschitz conditions.