Learning Fair Node Representations with Graph Counterfactual Fairness.
Jing Ma|Ruocheng Guo|Mengting Wan|Longqi Yang|Aidong Zhang|Jundong Li
| Anthology ID: | DBLP:conf/wsdm/MaGWYZL22 |
|---|---|
| Volume: | WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022 |
| Year: | 2022 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 695-703 |
| URL: | https://doi.org/10.1145/3488560.3498391 |
| DOI: | https://doi.org/10.1145/3488560.3498391 |
| DBLP: | conf/wsdm/MaGWYZL22 |
| BibTeX: |
@inproceedings{ma-2022-learning,
author = {Jing Ma and
Ruocheng Guo and
Mengting Wan and
Longqi Yang and
Aidong Zhang and
Jundong Li},
editor = {K. Sel\c{c}uk Candan and
Huan Liu and
Leman Akoglu and
Xin Dong and
Jiliang Tang},
title = {{Learning Fair Node Representations with Graph Counterfactual Fairness}},
booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}},
pages = {695--703},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3488560.3498391},
doi = {https://doi.org/10.1145/3488560.3498391}
}