FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance.
Minh Phu Vuong|Young-Ju Lee|Iván Ojeda-Ruiz|Chul-Ho Lee
| Anthology ID: | DBLP:conf/cikm/VuongLOL25 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 2935-2944 |
| URL: | https://doi.org/10.1145/3746252.3761320 |
| DOI: | https://doi.org/10.1145/3746252.3761320 |
| DBLP: | conf/cikm/VuongLOL25 |
| BibTeX: |
@inproceedings{vuong-2025-fairad,
author = {Minh Phu Vuong and
Young-Ju Lee and
Iv\'{a}n Ojeda-Ruiz and
Chul-Ho Lee},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {2935--2944},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761320},
doi = {https://doi.org/10.1145/3746252.3761320}
}