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.
Mode-wise principal subspace pursuit and ma- trix spiked covariance model.Journal of the Royal Statistical Society Series B: Statistical Methodology, 87(1):232–255, 2025b
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A two-step spectral embedding procedure that removes irrelevant components from a knowledge matrix then projects to recover shared and heterogeneous signals for rare-disease clinical concept and patient embeddings.
A functional tensor model with common invariant subspaces and RKHS estimation for analyzing dynamic multilayer networks, applied to bike-share and food-trade data.
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Enhancing Spectral Embedding through Robust and Flexible Knowledge Transfer in Electronic Health Records
A two-step spectral embedding procedure that removes irrelevant components from a knowledge matrix then projects to recover shared and heterogeneous signals for rare-disease clinical concept and patient embeddings.