Debias Once for All: A Data-Centric Strategy for Fair Machine Learning.
Yezi Liu|Hanning Chen|Yanning Shen|Mohsen Imani
| Anthology ID: | DBLP:conf/wsdm/LiuCSI26 |
|---|---|
| Volume: | Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026 |
| Year: | 2026 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 447-457 |
| URL: | https://doi.org/10.1145/3773966.3778010 |
| DOI: | https://doi.org/10.1145/3773966.3778010 |
| DBLP: | conf/wsdm/LiuCSI26 |
| BibTeX: |
@inproceedings{liu-2026-debias,
author = {Yezi Liu and
Hanning Chen and
Yanning Shen and
Mohsen Imani},
title = {{Debias Once for All: A Data-Centric Strategy for Fair Machine Learning}},
booktitle = {{Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026}},
pages = {447--457},
publisher = {ACM},
year = {2026},
url = {https://doi.org/10.1145/3773966.3778010},
doi = {https://doi.org/10.1145/3773966.3778010}
}