research
∙
07/19/2022
A coherence parameter characterizing generative compressed sensing with Fourier measurements
In Bora et al. (2017), a mathematical framework was developed for compre...
share
research
∙
10/30/2021
Beyond Independent Measurements: General Compressed Sensing with GNN Application
We consider the problem of recovering a structured signal 𝐱∈ℝ^n from noi...
research
∙
12/23/2020
NBIHT: An Efficient Algorithm for 1-bit Compressed Sensing with Optimal Error Decay Rate
The Binary Iterative Hard Thresholding (BIHT) algorithm is a popular rec...
research
∙
10/17/2020
On the best choice of Lasso program given data parameters
Generalized compressed sensing (GCS) is a paradigm in which a structured...
research
∙
01/28/2020
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications
Random linear mappings are widely used in modern signal processing, comp...
research
∙
10/30/2019
Weighted matrix completion from non-random, non-uniform sampling patterns
We study the matrix completion problem when the observation pattern is d...
research
∙
12/13/2018
Tight Analyses for Non-Smooth Stochastic Gradient Descent
Consider the problem of minimizing functions that are Lipschitz and stro...
research
∙
10/29/2018
Parameter instability regimes for sparse proximal denoising programs
Compressed sensing theory explains why Lasso programs recover structured...
research
∙
03/31/2018
Learning tensors from partial binary measurements
In this paper we generalize the 1-bit matrix completion problem to highe...
research
∙
11/14/2017
Near-optimal sample complexity for convex tensor completion
We analyze low rank tensor completion (TC) using noisy measurements of a...
research
∙
05/31/2016