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20162020
most citedSpectral Compressed Sensing via Projected Gradient Descent

3 citations · 8 across the 4 of their papers we have counts for

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cs.IT20193 cited

Exact matrix completion based on low rank Hankel structure in the Fourier domain

Jinchi Chen, Weiguo Gao, Ke Wei

Matrix completion is about recovering a matrix from its partial revealed entries, and it can often be achieved by exploiting the inherent simplicity or low dimensional structure of…

cs.IT2018

Towards the optimal construction of a loss function without spurious local minima for solving quadratic equations

Zhenzhen Li, Jian-Feng Cai, Ke Wei

The problem of finding a vector which obeys a set of quadratic equations , , plays an important role in many applications. In this paper we co…

cs.IT2017

Painless Breakups -- Efficient Demixing of Low Rank Matrices

Thomas Strohmer, Ke Wei

Assume we are given a sum of linear measurements of different rank- matrices of the form . When and under which conditions is it po…

cs.IT2016

Rapid, Robust, and Reliable Blind Deconvolution via Nonconvex Optimization

Xiaodong Li, Shuyang Ling, Thomas Strohmer +1

We study the question of reconstructing two signals and from their convolution . This problem, known as {\em blind deconvolution}, pervades many areas of scien…

cs.IT2016

Fast and Provable Algorithms for Spectrally Sparse Signal Reconstruction via Low-Rank Hankel Matrix Completion

Jian-Feng Cai, Tianming Wang, Ke Wei

A spectrally sparse signal of order is a mixture of damped or undamped complex sinusoids. This paper investigates the problem of reconstructing spectrally sparse signals fr…