Anonymity Can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-Label Graphs

Duan et al. "Anonymity Can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-Label Graphs." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022. doi:10.1007/978-3-031-26390-3_2

[Duan et al. "Anonymity Can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-Label Graphs." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022.](https://mlanthology.org/ecmlpkdd/2022/duan2022ecmlpkdd-anonymity/) doi:10.1007/978-3-031-26390-3_2

@inproceedings{duan2022ecmlpkdd-anonymity,
  title     = {{Anonymity Can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-Label Graphs}},
  author    = {Duan, Yijun and Liu, Xin and Jatowt, Adam and Yu, Haitao and Lynden, Steven J. and Kim, Kyoung-Sook and Matono, Akiyoshi},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2022},
  pages     = {20-36},
  doi       = {10.1007/978-3-031-26390-3_2},
  url       = {https://mlanthology.org/ecmlpkdd/2022/duan2022ecmlpkdd-anonymity/}
}