Jaemin Shin, Yuanchun Li, Yunxin Liu, Sung-Ju Lee. FedBalancer: data and pace control for efficient federated learning on heterogeneous clients. In Nirupama Bulusu, Ehsan Aryafar, Aruna Balasubramanian, Junehwa Song, editors, MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services, Portland, Oregon, 27 June 2022 - 1 July 2022. pages 436-449, ACM, 2022. [doi]
@inproceedings{ShinLLL22,
title = {FedBalancer: data and pace control for efficient federated learning on heterogeneous clients},
author = {Jaemin Shin and Yuanchun Li and Yunxin Liu and Sung-Ju Lee},
year = {2022},
doi = {10.1145/3498361.3538917},
url = {https://doi.org/10.1145/3498361.3538917},
researchr = {https://researchr.org/publication/ShinLLL22},
cites = {0},
citedby = {0},
pages = {436-449},
booktitle = {MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services, Portland, Oregon, 27 June 2022 - 1 July 2022},
editor = {Nirupama Bulusu and Ehsan Aryafar and Aruna Balasubramanian and Junehwa Song},
publisher = {ACM},
isbn = {978-1-4503-9185-6},
}