4 papers
Feature Weaken: Vicinal Data Augmentation for Classification
Songhao Jiang, Yan Chu, Tianxing Ma +1
Deep learning usually relies on training large-scale data samples to achieve better performance. However, over-fitting based on training data always remains a problem. Scholars hav…
Tensor completion via nonconvex tensor ring rank minimization with guaranteed convergence
Meng Ding, Ting-Zhu Huang, Xi-Le Zhao +1
In recent studies, the tensor ring (TR) rank has shown high effectiveness in tensor completion due to its ability of capturing the intrinsic structure within high-order tensors. A…
Tensor train rank minimization with nonlocal self-similarity for tensor completion
Meng Ding, Ting-Zhu Huang, Xi-Le Zhao +2
The tensor train (TT) rank has received increasing attention in tensor completion due to its ability to capture the global correlation of high-order tensors ().…
Tensor N-tubal rank and its convex relaxation for low-rank tensor recovery
Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao +3
As low-rank modeling has achieved great success in tensor recovery, many research efforts devote to defining the tensor rank. Among them, the recent popular tensor tubal rank, defi…