61 citations · 167 across the 16 of their papers we have counts for
5 papers · 1 filter
Sparse PCA: Phase Transitions in the Critical Regime
Michael J. Feldman, Theodor Misiakiewicz, Elad Romanov
This work studies estimation of sparse principal components in high dimensions. Specifically, we consider a class of estimators based on kernel PCA, generalizing the covariance thr…
The High-Dimensional Asymptotics of Principal Component Regression
Alden Green, Elad Romanov
We study principal components regression (PCR) in an asymptotic high-dimensional regression setting, where the number of data points is proportional to the dimension. We derive exa…
Matrix Denoising with Partial Noise Statistics: Optimal Singular Value Shrinkage of Spiked F-Matrices
Matan Gavish, William Leeb, Elad Romanov
We study the problem of estimating a large, low-rank matrix corrupted by additive noise of unknown covariance, assuming one has access to additional side information in the form of…
Tyler's and Maronna's M-estimators: Non-Asymptotic Concentration Results
Elad Romanov, Gil Kur, Boaz Nadler
Tyler's and Maronna's M-estimators, as well as their regularized variants, are popular robust methods to estimate the scatter or covariance matrix of a multivariate distribution. I…
ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise
David L. Donoho, Matan Gavish, Elad Romanov
We derive a formula for optimal hard thresholding of the singular value decomposition in the presence of correlated additive noise; although it nominally involves unobservables, we…