How Few Davids Improve One Goliath: Federated Learning in Resource-Skewed Edge Computing Environments.
Jiayun Zhang|Shuheng Li|Haiyu Huang|Zihan Wang|Xiaohan Fu|Dezhi Hong|Rajesh K. Gupta|Jingbo Shang
| Anthology ID: | DBLP:conf/www/ZhangLHWFH0S24 |
|---|---|
| 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: | 2976-2985 |
| URL: | https://doi.org/10.1145/3589334.3645544 |
| DOI: | https://doi.org/10.1145/3589334.3645544 |
| DBLP: | conf/www/ZhangLHWFH0S24 |
| BibTeX: |
@inproceedings{zhang-2024-davids,
author = {Jiayun Zhang and
Shuheng Li and
Haiyu Huang and
Zihan Wang and
Xiaohan Fu and
Dezhi Hong and
Rajesh K. Gupta and
Jingbo Shang},
editor = {Tat-Seng Chua and
Chong-Wah Ngo and
Ravi Kumar and
Hady Wirawan Lauw and
Roy Ka-Wei Lee},
title = {{How Few Davids Improve One Goliath: Federated Learning in Resource-Skewed Edge Computing Environments}},
booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}},
pages = {2976--2985},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3589334.3645544},
doi = {https://doi.org/10.1145/3589334.3645544}
}