118 citations · 222 across the 9 of their papers we have counts for
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cs.LG2020
Graph Metric Learning via Gershgorin Disc Alignment
Cheng Yang, Gene Cheung, Wei Hu
We propose a fast general projection-free metric learning framework, where the minimization objective is a convex differentiable f…
cs.LG2019
Joint Learning of Graph Representation and Node Features in Graph Convolutional Neural Networks
Jiaxiang Tang, Wei Hu, Xiang Gao +1
Graph Convolutional Neural Networks (GCNNs) extend classical CNNs to graph data domain, such as brain networks, social networks and 3D point clouds. It is critical to identify an a…
cs.LG2019
Exploring Structure-Adaptive Graph Learning for Robust Semi-Supervised Classification
Xiang Gao, Wei Hu, Zongming Guo
Graph Convolutional Neural Networks (GCNNs) are generalizations of CNNs to graph-structured data, in which convolution is guided by the graph topology. In many cases where graphs a…