research
∙
05/27/2023
On the Noise Sensitivity of the Randomized SVD
The randomized singular value decomposition (R-SVD) is a popular sketchi...
share
research
∙
11/02/2022
Matrix Denoising with Partial Noise Statistics: Optimal Singular Value Shrinkage of Spiked F-Matrices
We study the problem of estimating a large, low-rank matrix corrupted by...
research
∙
06/21/2022
Tyler's and Maronna's M-estimators: Non-Asymptotic Concentration Results
Tyler's and Maronna's M-estimators, as well as their regularized variant...
research
∙
02/15/2022
On the Role of Channel Capacity in Learning Gaussian Mixture Models
This paper studies the sample complexity of learning the k unknown cente...
research
∙
10/04/2021
Spiked Covariance Estimation from Modulo-Reduced Measurements
Consider the rank-1 spiked model: X=√(ν)ξu+ Z, where ν is the spike inte...
research
∙
05/11/2021
On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel
Motivated by applications in unsourced random access, this paper develop...
research
∙
09/25/2020
ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise
We derive a formula for optimal hard thresholding of the singular value ...
research
∙
07/22/2020
Multi-reference alignment in high dimensions: sample complexity and phase transition
Multi-reference alignment entails estimating a signal in ℝ^L from its ci...
research
∙
03/28/2019
Above the Nyquist Rate, Modulo Folding Does Not Hurt
We consider the problem of recovering a continuous-time bandlimited sign...
research
∙
01/29/2019
Blind Unwrapping of Modulo Reduced Gaussian Vectors: Recovering MSBs from LSBs
We consider the problem of recovering n i.i.d samples from a zero mean m...
research
∙
11/06/2018
Optimal singular value shrinkage with noise homogenization
We derive the optimal singular values for prediction in the spiked model...
research
∙
03/08/2018