10 citations · 29 across the 7 of their papers we have counts for
7 papers
A coherence parameter characterizing generative compressed sensing with Fourier measurements
Aaron Berk, Simone Brugiapaglia, Babhru Joshi +3
In Bora et al. (2017), a mathematical framework was developed for compressed sensing guarantees in the setting where the measurement matrix is Gaussian and the signal structure is…
Polar Deconvolution of Mixed Signals
Zhenan Fan, Halyun Jeong, Babhru Joshi +1
The signal demixing problem seeks to separate a superposition of multiple signals into its constituent components. This paper studies a two-stage approach that first decompresses a…
Bilinear Compressed Sensing under known Signs via Convex Programming
Alireza Aghasi, Ali Ahmed, Paul Hand +1
We consider the bilinear inverse problem of recovering two vectors, and , from their entrywise product. We consider…
Global Guarantees for Blind Demodulation with Generative Priors
Paul Hand, Babhru Joshi
We study a deep learning inspired formulation for the blind demodulation problem, which is the task of recovering two unknown vectors from their entrywise multiplication. We consid…
A convex program for bilinear inversion of sparse vectors
Alireza Aghasi, Ali Ahmed, Paul Hand +1
We consider the bilinear inverse problem of recovering two vectors, and , from their entrywise product. We consider t…
BranchHull: Convex bilinear inversion from the entrywise product of signals with known signs
Alireza Aghasi, Ali Ahmed, Paul Hand +1
We consider the bilinear inverse problem of recovering two vectors, and , in from their entrywise product. For the case where the vectors have known signs and…
A Convex Program for Mixed Linear Regression with a Recovery Guarantee for Well-Separated Data
Paul Hand, Babhru Joshi
We introduce a convex approach for mixed linear regression over features. This approach is a second-order cone program, based on L1 minimization, which assigns an estimate regr…