56 citations · 81 across the 3 of their papers we have counts for
4 papers
Rethinking Propagation for Unsupervised Graph Domain Adaptation
Meihan Liu, Zeyu Fang, Zhen Zhang +4
Unsupervised Graph Domain Adaptation (UGDA) aims to transfer knowledge from a labelled source graph to an unlabelled target graph in order to address the distribution shifts betwee…
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions
Sheng Zhou, Hongjia Xu, Zhuonan Zheng +7
Clustering is a fundamental machine learning task which has been widely studied in the literature. Classic clustering methods follow the assumption that data are represented as fea…
Distilling Holistic Knowledge with Graph Neural Networks
Sheng Zhou, Yucheng Wang, Defang Chen +4
Knowledge Distillation (KD) aims at transferring knowledge from a larger well-optimized teacher network to a smaller learnable student network.Existing KD methods have mainly consi…
HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding
Sheng Zhou, Jiajun Bu, Xin Wang +2
Heterogeneous information network (HIN) embedding has recently attracted much attention due to its effectiveness in dealing with the complex heterogeneous data. Meta path, which co…