3 papers
math.ST2019
On Inferences from Completed Data
Jamie Haddock, Denali Molitor, Deanna Needell +3
Matrix completion has become an extremely important technique as data scientists are routinely faced with large, incomplete datasets on which they wish to perform statistical infer…
cs.IT2016
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…
cs.IT2016
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…