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Faithful Edge Federated Learning: Scalability and Privacy

Faithful Edge Federated Learning: Scalability and Privacy

30 June 2021
Meng Zhang
Ermin Wei
R. Berry
    FedML
ArXivPDFHTML

Papers citing "Faithful Edge Federated Learning: Scalability and Privacy"

5 / 5 papers shown
Title
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and
  Applications
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
Azim Akhtarshenas
Mohammad Ali Vahedifar
Navid Ayoobi
B. Maham
Tohid Alizadeh
Sina Ebrahimi
David López-Pérez
FedML
28
5
0
08 Oct 2023
Collaborative Machine Learning with Incentive-Aware Model Rewards
Collaborative Machine Learning with Incentive-Aware Model Rewards
Rachael Hwee Ling Sim
Yehong Zhang
M. Chan
Hsiang Low
FedML
117
123
0
24 Oct 2020
Convergence of Update Aware Device Scheduling for Federated Learning at
  the Wireless Edge
Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edge
M. Amiri
Deniz Gunduz
Sanjeev R. Kulkarni
H. Vincent Poor
92
170
0
28 Jan 2020
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
144
1,687
0
14 Apr 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the
  Polyak-Łojasiewicz Condition
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi
J. Nutini
Mark W. Schmidt
139
1,199
0
16 Aug 2016
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