10 citations · 21 across the 10 of their papers we have counts for
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cs.IT2020
Linear Regression without Correspondences via Concave Minimization
Liangzu Peng, Manolis C. Tsakiris
Linear regression without correspondences concerns the recovery of a signal in the linear regression setting, where the correspondences between the observations and the linear func…
cs.LG2020★ 9 cited
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…