10 citations · 12 across the 9 of their papers we have counts for
4 papers · 1 filter
Blind Super-resolution of Point Sources via Projected Gradient Descent
Sihan Mao, Jinchi Chen
Blind super-resolution can be cast as a low rank matrix recovery problem by exploiting the inherent simplicity of the signal and the low dimensional structure of point spread funct…
Blind Super-resolution via Projected Gradient Descent
Sihan Mao, Jinchi Chen
Blind super-resolution can be cast as low rank matrix recovery problem by exploiting the inherent simplicity of the signal. In this paper, we develop a simple yet efficient nonconv…
Blind super-resolution of point sources via fast iterative hard thresholding
Zengying Zhu, Jinchi Chen, Weiguo Gao
In this work, we develop a provable fast algorithm for blind super-resolution based on the low rank structure of vectorized Hankel matrix associated with the target matrix. Theoret…
Implicit Regularization and Entrywise Convergence of Riemannian Optimization for Low Tucker-Rank Tensor Completion
Haifeng Wang, Jinchi Chen, Ke Wei
This paper is concerned with the low Tucker-rank tensor completion problem, which is about reconstructing a tensor of low multilinear rank f…