53 citations · 143 across the 24 of their papers we have counts for
4 papers · 1 filter
IRLS for Sparse Recovery Revisited: Examples of Failure and a Remedy
Aleksandr Y. Aravkin, James V. Burke, Daiwei He
Compressed sensing is a central topic in signal processing with myriad applications, where the goal is to recover a signal from as few observations as possible. Iterative re-weight…
A study of convex convex-composite functions via infimal convolution with applications
James V. Burke, Tim Hoheisel, Quang V. Nguyen
In this note we provide a full conjugacy and subdifferential calculus for convex convex-composite functions in finite-dimensional space. Our approach, based on infimal convolution…
On the Global Minimizers of Real Robust Phase Retrieval with Sparse Noise
Aleksandr Aravkin, James Burke, Daiwei He
We study a class of real robust phase retrieval problems under a Gaussian assumption on the coding matrix when the received signal is sparsely corrupted by noise. The goal is to es…
Robust Singular Smoothers For Tracking Using Low-Fidelity Data
Jonathan Jonker, Aleksandr Aravkin, James V. Burke +2
Tracking underwater autonomous platforms is often difficult because of noisy, biased, and discretized input data. Classic filters and smoothers based on standard assumptions of Gau…