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} }