Cargando…
A Cluster-Driven Adaptive Training Approach for Federated Learning
Federated learning (FL) is a promising collaborative learning approach in edge computing, reducing communication costs and addressing the data privacy concerns of traditional cloud-based training. Owing to this, diverse studies have been conducted to distribute FL into industry. However, there still...
Autores principales: | Jeong, Younghwan, Kim, Taeyoon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502390/ https://www.ncbi.nlm.nih.gov/pubmed/36146408 http://dx.doi.org/10.3390/s22187061 |
Ejemplares similares
-
Deep Federated Adaptation: An Adaptative Residential Load Forecasting Approach with Federated Learning
por: Shi, Yuan, et al.
Publicado: (2022) -
Genetic CFL: Hyperparameter Optimization in Clustered Federated Learning
por: Agrawal, Shaashwat, et al.
Publicado: (2021) -
Multinational Federated Learning Approach to Train ECG and Echocardiogram Models for Hypertrophic Cardiomyopathy Detection
por: Goto, Shinichi, et al.
Publicado: (2022) -
Adaptive Broadcasting Method Using Neighbor Type Information in Wireless Sensor Networks
por: Jeong, Hyocheol, et al.
Publicado: (2011) -
Federated Reinforcement Learning for Training Control Policies on Multiple IoT Devices
por: Lim, Hyun-Kyo, et al.
Publicado: (2020)