24 citations · 87 across the 18 of their papers we have counts for
9 papers · 1 filter
Simpler Gradient Methods for Blind Super-Resolution with Lower Iteration Complexity
Jinsheng Li, Wei Cui, Xu Zhang
We study the problem of blind super-resolution, which can be formulated as a low-rank matrix recovery problem via vectorized Hankel lift (VHL). The previous gradient descent method…
Data-Time Tradeoffs for Optimal k-Thresholding Algorithms in Compressed Sensing
Jialiang Xu, Xu Zhang
Optimal -thresholding algorithms are a class of -sparse signal recovery algorithms that overcome the shortcomings of traditional hard thresholding algorithms caused by the os…
Spectrally Sparse Signal Recovery via Hankel Matrix Completion with Prior Information
Xu Zhang, Yulong Liu, Wei Cui
This paper studies the problem of reconstructing spectrally sparse signals from a small random subset of time domain samples via low-rank Hankel matrix completion with the aid of p…
Matrix Completion with Prior Subspace Information via Maximizing Correlation
Xu Zhang, Wei Cui, Yulong Liu
This paper studies the problem of completing a low-rank matrix from a few of its random entries with the aid of prior information. We suggest a strategy to incorporate prior inform…
Covariance Matrix Estimation from Correlated Sub-Gaussian Samples
Xu Zhang, Wei Cui, Yulong Liu
This paper studies the problem of estimating a covariance matrix from correlated sub-Gaussian samples. We consider using the correlated sample covariance matrix estimator to approx…
Compressive Multidimensional Harmonic Retrieval with Prior Knowledge
Yinchuan Li, Xu Zhang, Zegang Ding +1
This paper concerns the problem of estimating multidimensional (MD) frequencies using prior knowledge of the signal spectral sparsity from partial time samples. In many application…
Covariance Matrix Estimation from Linearly-Correlated Gaussian Samples
Wei Cui, Xu Zhang, Yulong Liu
Covariance matrix estimation concerns the problem of estimating the covariance matrix from a collection of samples, which is of extreme importance in many applications. Classical r…
Recovery of Structured Signals with Prior Information via Maximizing Correlation
Xu Zhang, Wei Cui, Yulong Liu
This paper considers the problem of recovering a structured signal from a relatively small number of noisy measurements with the aid of a similar signal which is known beforehand.…
Compressed Sensing with Prior Information via Maximizing Correlation
Xu Zhang, Wei Cui, Yulong Liu
Compressed sensing (CS) with prior information concerns the problem of reconstructing a sparse signal with the aid of a similar signal which is known beforehand. We consider a new…