Enhancing Fairness in Meta-learned User Modeling via Adaptive Sampling.
Zheng Zhang|Qi Liu|Zirui Hu|Yi Zhan|Zhenya Huang|Weibo Gao|Qingyang Mao
| Anthology ID: | DBLP:conf/www/ZhangLHZHGM24 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024 |
| Year: | 2024 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 3241-3252 |
| URL: | https://doi.org/10.1145/3589334.3645369 |
| DOI: | https://doi.org/10.1145/3589334.3645369 |
| DBLP: | conf/www/ZhangLHZHGM24 |
| BibTeX: |
@inproceedings{zhang-2024-enhancing,
author = {Zheng Zhang and
Qi Liu and
Zirui Hu and
Yi Zhan and
Zhenya Huang and
Weibo Gao and
Qingyang Mao},
editor = {Tat-Seng Chua and
Chong-Wah Ngo and
Ravi Kumar and
Hady Wirawan Lauw and
Roy Ka-Wei Lee},
title = {{Enhancing Fairness in Meta-learned User Modeling via Adaptive Sampling}},
booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}},
pages = {3241--3252},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3589334.3645369},
doi = {https://doi.org/10.1145/3589334.3645369}
}