Dealing with Noisy Data in Federated Learning: An Incentive Mechanism with Flexible Pricing.

Hengzhi Wang|Haoran Chen|Minghe Ma|Laizhong Cui


Anthology ID:DBLP:conf/www/WangCMC25
Volume:Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025
Year:2025
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:4432-4441
URL:https://doi.org/10.1145/3696410.3714961
DOI:https://doi.org/10.1145/3696410.3714961
DBLP:conf/www/WangCMC25
BibTeX:
@inproceedings{wang-2025-dealing, author = {Hengzhi Wang and Haoran Chen and Minghe Ma and Laizhong Cui}, editor = {Guodong Long and Michale Blumestein and Yi Chang and Liane Lewin-Eytan and Zi Huang and Elad Yom-Tov}, title = {{Dealing with Noisy Data in Federated Learning: An Incentive Mechanism with Flexible Pricing}}, booktitle = {{Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025}}, pages = {4432--4441}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3696410.3714961}, doi = {https://doi.org/10.1145/3696410.3714961} }