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.
| Original language | English |
|---|---|
| Pages (from-to) | 1118-1120 |
| Number of pages | 3 |
| Journal | Journal of Korean Institute of Communications and Information Sciences |
| Volume | 49 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - Aug 2024 |
Bibliographical note
Publisher Copyright:© 2024, Korean Institute of Communications and Information Sciences. All rights reserved.
Keywords
- Federated Learning
- non-IID problem
- training accuracy
Fingerprint
Dive into the research topics of 'Adaptive Federated Learning in Non-IID Data Environment'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver