Joint structure feature exploration and regularization for multi-task graph classification

By Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu. 2016

55 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Shirui Pan
2. Guodong Long
3. Chengqi Zhang
4. Jing Jiang
5. Ruiqi Hu
6. Xingquan Zhu
7. Sai-Fu Fung
8. C. Wang

In Computer Vision and Pattern Recognition

1. Shirui Pan
2. Jing Jiang
3. Xingquan Zhu
4. Guodong Long
5. Ruiqi Hu
6. Chengqi Zhang

Citations in the corpus

• Learning Graph Embedding With Adversarial Training Methods (2019, background): “In a variety of graph applications, such as social networks, citation networks, proteinprotein interaction networks, graph data analysis plays an important role in various data mining tasks including classification [1], clustering [2], recommendation [3], [4], [5], and graph classification [6], [7].”
• MGAE: Marginalized Graph Autoencoder for Graph Clustering (2017, background): “Graph or network analytics has been a long-standing research topic in machine learning [13, 22–24, 26, 33, 35, 40].”