49 citations · 75 across the 9 of their papers we have counts for
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cs.LG2023★ 2 cited
Graph Entropy Minimization for Semi-supervised Node Classification
Yi Luo, Guangchun Luo, Ke Qin +1
Node classifiers are required to comprehensively reduce prediction errors, training resources, and inference latency in the industry. However, most graph neural networks (GNN) conc…
cs.LG2022
Unifying Label-inputted Graph Neural Networks with Deep Equilibrium Models
Yi Luo, Guiduo Duan, Guangchun Luo +1
The success of Graph Neural Networks (GNN) in learning on non-Euclidean data arouses many subtopics, such as Label-inputted GNN (LGNN) and Implicit GNN (IGNN). LGNN, explicitly inp…
cs.LG2020★ 4 cited
Adversarial Privacy Preserving Graph Embedding against Inference Attack
Kaiyang Li, Guangchun Luo, Yang Ye +3
Recently, the surge in popularity of Internet of Things (IoT), mobile devices, social media, etc. has opened up a large source for graph data. Graph embedding has been proved extre…