Conference Tutorials

Tutorials

1. Causal Inference with Latent Variables: Recent Advances and Future Prospectives
   Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
   

2. Fairness in Graph Machine Learning: Recent Advances and Future Prospectives
   Yushun Dong, Oyku Deniz Kose, Yanning Shen, Jundong Li
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.

3. Data-Efficient Graph Learning
   Kaize Ding, Jundong Li, Chuxu Zhang, Jie Tang, and Huan Liu
   SIAM International Conference on Data Mining (SDM), 2023.

4. Machine Learning for Causal Inference
   Zhixuan Chu, Jing Ma, Jundong Li, Sheng Li
   AAAI Conference on Artificial Intelligence (AAAI), 2023.

5. Fairness in Graph Mining: Metrics, Algorithms, and Applications
   Yushun Dong, Jing Ma, Chen Chen, Jundong Li
   IEEE International Conference on Data Mining (ICDM), 2022.

6. Graph Minimally-supervised Learning
   Kaize Ding, Jundong Li, Nitesh Chawla, Huan Liu
   ACM International Conference on Web Search and Data Mining (WSDM), 2022.

7. Data Efficient Learning on Graphs
   Chuxu Zhang, Jundong Li, Meng Jiang
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.

8. Learning From Networks: Algorithms, Theory, and Applications
   Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019.

9. Recent Advances in Feature Selection: A Data Perspective
   Jundong Li, Jiliang Tang, Huan Liu
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017.