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An On-Device Federated Learning Approach for Cooperative Model Update
  between Edge Devices
v1v2v3v4v5 (latest)

An On-Device Federated Learning Approach for Cooperative Model Update between Edge Devices

IEEE Access (IEEE Access), 2020
27 February 2020
Rei Ito
Mineto Tsukada
Hiroki Matsutani
    FedML
ArXiv (abs)PDFHTML

Papers citing "An On-Device Federated Learning Approach for Cooperative Model Update between Edge Devices"

4 / 4 papers shown
Onboard Optimization and Learning: A Survey
Onboard Optimization and Learning: A Survey
Monirul Islam Pavel
Siyi Hu
Mahardhika Pratama
Ryszard Kowalczyk
435
2
0
07 May 2025
ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud
  Continuum
ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud ContinuumIEEE International Conference on Cluster Computing (CLUSTER), 2023
Daniel Rosendo
M. Mattoso
Alexandru Costan
Renan Souza
Débora B. Pina
P. Valduriez
Gabriel Antoniu
267
7
0
20 Jul 2023
Fast Deep Autoencoder for Federated learning
Fast Deep Autoencoder for Federated learningPattern Recognition (Pattern Recogn.), 2022
David Novoa-Paradela
O. Fontenla-Romero
Bertha Guijarro-Berdiñas
FedML
233
30
0
10 Jun 2022
Machine Learning for the Control and Monitoring of Electric Machine
  Drives: Advances and Trends
Machine Learning for the Control and Monitoring of Electric Machine Drives: Advances and TrendsIEEE Open Journal of Industry Applications (JOIA), 2021
Shen Zhang
Oliver Wallscheid
Mario Porrmann
230
66
0
11 Oct 2021
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