294 citations · 389 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
Average-case Hardness of RIP Certification
Tengyao Wang, Quentin Berthet, Yaniv Plan
The restricted isometry property (RIP) for design matrices gives guarantees for optimal recovery in sparse linear models. It is of high interest in compressed sensing and statistic…
A simple tool for bounding the deviation of random matrices on geometric sets
Christopher Liaw, Abbas Mehrabian, Yaniv Plan +1
Let be an isotropic, sub-gaussian matrix. We prove that the process has sub-gaussian increments. Using this, we show that for a…