3 citations · 10 across the 20 of their papers we have counts for
5 papers · 1 filter
Robust recovery of bandlimited graph signals via randomized dynamical sampling
Longxiu Huang, Deanna Needell, Sui Tang
Heat diffusion processes have found wide applications in modelling dynamical systems over graphs. In this paper, we consider the recovery of a -bandlimited graph signal that is…
Weighted matrix completion from non-random, non-uniform sampling patterns
Simon Foucart, Deanna Needell, Reese Pathak +2
We study the matrix completion problem when the observation pattern is deterministic and possibly non-uniform. We propose a simple and efficient debiased projection scheme for reco…
An Approximate Message Passing Framework for Side Information
Anna Ma, You, Zhou +3
Approximate message passing (AMP) methods have gained recent traction in sparse signal recovery. Additional information about the signal, or \emph{side information} (SI), is common…
One-Bit Compressive Sensing of Dictionary-Sparse Signals
Rich Baraniuk, Simon Foucart, Deanna Needell +2
One-bit compressive sensing has extended the scope of sparse recovery by showing that sparse signals can be accurately reconstructed even when their linear measurements are subject…
Optimizing quantization for Lasso recovery
Xiaoyi Gu, Shenyinying Tu, Hao-Jun Michael Shi +3
This letter is focused on quantized Compressed Sensing, assuming that Lasso is used for signal estimation. Leveraging recent work, we provide a framework to optimize the quantizati…