FairRegBoost: An End-to-End Data Processing Framework for Fair and Scalable Regression.

Nico Lässig|Melanie Herschel


Anthology ID:DBLP:conf/cikm/LassigH25
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:1417-1427
URL:https://doi.org/10.1145/3746252.3761277
DOI:https://doi.org/10.1145/3746252.3761277
DBLP:conf/cikm/LassigH25
BibTeX:
@inproceedings{lassig-2025-fairregboost, author = {Nico L\"{a}ssig and Melanie Herschel}, editor = {Carl Yang and Meeyoung Cha 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 = {{FairRegBoost: An End-to-End Data Processing Framework for Fair and Scalable Regression}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {1417--1427}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3761277}, doi = {https://doi.org/10.1145/3746252.3761277} }