TY  - JOUR
T1  - Adaptive Federated Learning in Non-IID Data Environment
AU  - Lee, Jae-wook 
AU  - Ko, Haneul 
JO  - The Journal of Korean Institute of Communications and Information Sciences
PY  - 2024
DA  - 2024/1/1
DO  - 10.7840/kics.2024.49.8.1118
KW  - Federated learning
KW  - non-IID problem
KW  - training accuracy
AB  - 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.