@article{M32CB283D,
title = "Adaptive Federated Learning in Non-IID Data Environment",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2024",
issn = "1226-4717",
doi = "10.7840/kics.2024.49.8.1118",
author = "Jae-wook Lee, Haneul Ko",
keywords = "Federated learning, non-IID problem, training accuracy",
abstract = "In this paper, we propose the adaptive federated learning called FedA under non-IID data environment to guarantee the training accuracy and reduce training time. FedA adaptively selects the proper traditional federated learning scheme according to the non-IID degree. Also, we conduct the simulation to obtain the policy representing which federated learning scheme is configured according to the non-IID degree and to confirm the outperformance of our proposed scheme."
}