323 citations · 1k across the 34 of their papers we have counts for
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Support Recovery for Sparse Signals with Unknown Non-stationary Modulation
Youye Xie, Michael B. Wakin, Gongguo Tang
The problem of estimating a sparse signal from low dimensional noisy observations arises in many applications, including super resolution, signal deconvolution, and radar imaging.…
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk
Shuang Li, Gongguo Tang, Michael B. Wakin
The landscape of empirical risk has been widely studied in a series of machine learning problems, including low-rank matrix factorization, matrix sensing, matrix completion, and ph…
Provable Bregman-divergence based Methods for Nonconvex and Non-Lipschitz Problems
Qiuwei Li, Zhihui Zhu, Gongguo Tang +1
The (global) Lipschitz smoothness condition is crucial in establishing the convergence theory for most optimization methods. Unfortunately, most machine learning and signal process…
Spherical Principal Component Analysis
Kai Liu, Qiuwei Li, Hua Wang +1
Principal Component Analysis (PCA) is one of the most important methods to handle high dimensional data. However, most of the studies on PCA aim to minimize the loss after projecti…
Atomic Norm Denoising for Complex Exponentials with Unknown Waveform Modulations
Shuang Li, Michael B. Wakin, Gongguo Tang
Non-stationary blind super-resolution is an extension of the traditional super-resolution problem, which deals with the problem of recovering fine details from coarse measurements.…
Simultaneous Sparse Recovery and Blind Demodulation
Youye Xie, Michael B. Wakin, Gongguo Tang
The task of finding a sparse signal decomposition in an overcomplete dictionary is made more complicated when the signal undergoes an unknown modulation (or convolution in the comp…