Federated Learning Hyper-Parameter Tuning for Edge Computing
Edge computing is widely recognized as a crucial technology for the upcoming generation of communication networks and has garnered significant interest from both industry and academia. Compared to other offloading models like cloud computing, it provides faster data processing capabilities, enhanced...
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2023
|
| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/86742 |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares: Federated Learning Hyper-Parameter Tuning for Edge Computing
- Federated Learning Hyper-Parameter Tuning from a System Perspective
- FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
- Service Provision and Price Strategies in Edge Computing
- Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale
- Hyper Redundant Manipulators
- Algorithm Selection: From Meta-Learning to Hyper-Heuristics