Genetic CFL: Hyperparameter Optimization in Clustered Federated Learning
Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence. FL has the capability of revolutionizing machine learning (ML) but lacks in the practicality of implementation due to technological limitations, co...
Guardado en:
Autores principales: | Shaashwat Agrawal, Sagnik Sarkar, Mamoun Alazab, Praveen Kumar Reddy Maddikunta, Thippa Reddy Gadekallu, Quoc-Viet Pham |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Hindawi Limited
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/495259675b2345d1893d31851301e63a |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
The future of digital health with federated learning
por: Nicola Rieke, et al.
Publicado: (2020) -
Privacy-first health research with federated learning
por: Adam Sadilek, et al.
Publicado: (2021) -
Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study
por: Qi Dou, et al.
Publicado: (2021) -
Evaluation framework to guide implementation of AI systems into healthcare settings
por: Enrico Coiera, et al.
Publicado: (2021) -
An Efficient Parallelized Ontology Network-Based Semantic Similarity Measure for Big Biomedical Document Clustering
por: Meijing Li, et al.
Publicado: (2021)