10 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.CV2019
An Efficient Tensor Completion Method via New Latent Nuclear Norm
Jinshi Yu, Weijun Sun, Yuning Qiu +1
In tensor completion, the latent nuclear norm is commonly used to induce low-rank structure, while substantially failing to capture the global information due to the utilization of…
cs.CV2019★ 10 cited
Tensor-Ring Nuclear Norm Minimization and Application for Visual Data Completion
Jinshi Yu, Chao Li, Qibin Zhao +1
Tensor ring (TR) decomposition has been successfully used to obtain the state-of-the-art performance in the visual data completion problem. However, the existing TR-based completio…
cs.LG2018
Low-Rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling
Chao Li, Zhun Sun, Jinshi Yu +2
Although the convolutional neural networks (CNNs) have become popular for various image processing and computer vision task recently, it remains a challenging problem to reduce the…