4 papers
Improve Deep Image Inpainting by Emphasizing the Complexity of Missing Regions
Yufeng Wang, Dan Li, Cong Xu +1
Deep image inpainting research mainly focuses on constructing various neural network architectures or imposing novel optimization objectives. However, on the one hand, building a s…
An Orthogonal Classifier for Improving the Adversarial Robustness of Neural Networks
Cong Xu, Xiang Li, Min Yang
Neural networks are susceptible to artificially designed adversarial perturbations. Recent efforts have shown that imposing certain modifications on classification layer can improv…
Improve Adversarial Robustness via Weight Penalization on Classification Layer
Cong Xu, Dan Li, Min Yang
It is well-known that deep neural networks are vulnerable to adversarial attacks. Recent studies show that well-designed classification parts can lead to better robustness. However…
A Fast deflation Method for Sparse Principal Component Analysis via Subspace Projections
Cong Xu, Min Yang, Jin Zhang
The implementation of conventional sparse principal component analysis (SPCA) on high-dimensional data sets has become a time consuming work. In this paper, a series of subspace pr…