Fair Graph Representation Learning via Diverse Mixture-of-Experts.
Zheyuan Liu|Chunhui Zhang|Yijun Tian|Erchi Zhang|Chao Huang|Yanfang Ye|Chuxu Zhang
| Anthology ID: | DBLP:conf/www/0010Z0Z00Z23 |
|---|---|
| Volume: | Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023 |
| Year: | 2023 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 28-38 |
| URL: | https://doi.org/10.1145/3543507.3583207 |
| DOI: | https://doi.org/10.1145/3543507.3583207 |
| DBLP: | conf/www/0010Z0Z00Z23 |
| BibTeX: |
@inproceedings{liu-2023-fair,
author = {Zheyuan Liu and
Chunhui Zhang and
Yijun Tian and
Erchi Zhang and
Chao Huang and
Yanfang Ye and
Chuxu Zhang},
editor = {Ying Ding and
Jie Tang and
Juan F. Sequeda and
Lora Aroyo and
Carlos Castillo and
Geert-Jan Houben},
title = {{Fair Graph Representation Learning via Diverse Mixture-of-Experts}},
booktitle = {{Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}},
pages = {28--38},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3543507.3583207},
doi = {https://doi.org/10.1145/3543507.3583207}
}