37 citations · 47 across the 9 of their papers we have counts for
7 papers · 1 filter
Phase Retrieval of Low-Rank Matrices by Anchored Regression
Kiryung Lee, Sohail Bahmani, Yonina Eldar +1
We study the low-rank phase retrieval problem, where we try to recover a low-rank matrix from a series of phaseless linear measurements. This is a fourth-order inve…
Optimal Sample Complexity for Stable Matrix Recovery
Yanjun Li, Kiryung Lee, Yoram Bresler
Tremendous efforts have been made to study the theoretical and algorithmic aspects of sparse recovery and low-rank matrix recovery. This paper fills a theoretical gap in matrix rec…
Blind Gain and Phase Calibration via Sparse Spectral Methods
Yanjun Li, Kiryung Lee, Yoram Bresler
Blind gain and phase calibration (BGPC) is a bilinear inverse problem involving the determination of unknown gains and phases of the sensing system, and the unknown signal, jointly…
Spectral Methods for Passive Imaging: Non-asymptotic Performance and Robustness
Kiryung Lee, Felix Krahmer, Justin Romberg
We study the problem of passive imaging through convolutive channels. A scene is illuminated with an unknown, unstructured source, and the measured response is the convolution of t…
Identifiability in Blind Deconvolution with Subspace or Sparsity Constraints
Yanjun Li, Kiryung Lee, Yoram Bresler
Blind deconvolution (BD), the resolution of a signal and a filter given their convolution, arises in many applications. Without further constraints, BD is ill-posed. In practice, s…
Oblique Pursuits for Compressed Sensing
Kiryung Lee, Yoram Bresler, Marius Junge
Compressed sensing is a new data acquisition paradigm enabling universal, simple, and reduced-cost acquisition, by exploiting a sparse signal model. Most notably, recovery of the s…