Name
Abstract | ||
|---|---|---|
The ongoing deployments of the Internet of Things (IoT)-based smart applications are spurring the adoption of machine learning as a key technology enabler. To overcome the privacy and overhead challenges of centralized machine learning, there has been significant recent interest in the concept of federated learning. Federated learning offers on-device machine learning without the need to transfer ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MWC.011.2100003 | IEEE Wireless Communications |
Keywords | DocType | Volume |
Computational modeling,Privacy,Servers,Robustness,Performance evaluation,Machine learning,Industries | Journal | 28 |
Issue | ISSN | Citations |
5 | 1536-1284 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Latif U. Khan | 1 | 29 | 2.86 |
| Walid Saad | 2 | 4450 | 279.64 |
| Zhu Han | 3 | 11215 | 760.71 |
| Choong Seon Hong | 4 | 2044 | 277.88 |