37 citations · 47 across the 8 of their papers we have counts for
8 papers
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…
Generalized notions of sparsity and restricted isometry property. Part II: Applications
Marius Junge, Kiryung Lee
The restricted isometry property (RIP) is a universal tool for data recovery. We explore the implication of the RIP in the framework of generalized sparsity and group measurements…
Generalized notions of sparsity and restricted isometry property. Part I: A unified framework
Marius Junge, Kiryung Lee
The restricted isometry property (RIP) is an integral tool in the analysis of various inverse problems with sparsity models. Motivated by the applications of compressed sensing and…
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…