4 papers
Auto robust relative radiometric normalization via latent change noise modelling
Shiqi Liu, Lu Wang, Jie Lian +9
Relative radiometric normalization(RRN) of different satellite images of the same terrain is necessary for change detection, object classification/segmentation, and map-making task…
Modeling Heterogeneous Edges to Represent Networks with Graph Auto-Encoder
Lu Wang, Yu Song, Hong Huang +3
In the real world, networks often contain multiple relationships among nodes, manifested as the heterogeneity of the edges in the networks. We convert the heterogeneous networks in…
Label-Aware Graph Convolutional Networks
Hao Chen, Yue Xu, Feiran Huang +5
Recent advances in Graph Convolutional Networks (GCNs) have led to state-of-the-art performance on various graph-related tasks. However, most existing GCN models do not explicitly…
Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution
Shen-Huan Lyu, Lu Wang, Zhi-Hua Zhou
Recent research has used margin theory to analyze the generalization performance for deep neural networks (DNNs). The existed results are almost based on the spectrally-normalized…