9 citations · 26 across the 4 of their papers we have counts for
5 papers
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization
Chong You, Zhihui Zhu, Qing Qu +1
Recent advances have shown that implicit bias of gradient descent on over-parameterized models enables the recovery of low-rank matrices from linear measurements, even with no prio…
Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications
Qing Qu, Zhihui Zhu, Xiao Li +3
The problem of finding the sparsest vector (direction) in a low dimensional subspace can be considered as a homogeneous variant of the sparse recovery problem, which finds applicat…
Analysis of the Optimization Landscapes for Overcomplete Representation Learning
Qing Qu, Yuexiang Zhai, Xiao Li +2
We study nonconvex optimization landscapes for learning overcomplete representations, including learning (i) sparsely used overcomplete dictionaries and (ii) convolutional dictiona…
Short-and-Sparse Deconvolution -- A Geometric Approach
Yenson Lau, Qing Qu, Han-Wen Kuo +3
Short-and-sparse deconvolution (SaSD) is the problem of extracting localized, recurring motifs in signals with spatial or temporal structure. Variants of this problem arise in appl…
A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution
Qing Qu, Xiao Li, Zhihui Zhu
We study the multi-channel sparse blind deconvolution (MCS-BD) problem, whose task is to simultaneously recover a kernel and multiple sparse inputs $\{\mathbf x_i\}_{i=…