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  4. Cited By
Client Selection for Federated Learning with Heterogeneous Resources in
  Mobile Edge

Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

23 April 2018
Takayuki Nishio
Ryo Yonetani
    FedML
ArXivPDFHTML

Papers citing "Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge"

11 / 411 papers shown
Title
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals,
  Technology Integration, and State-of-the-Art
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art
Viet Quoc Pham
Fang Fang
H. Vu
Md. Jalil Piran
Mai Le
L. Le
W. Hwang
Z. Ding
23
597
0
20 Jun 2019
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with
  Edge Computing
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
Zhi Zhou
Xu Chen
En Li
Liekang Zeng
Ke Luo
Junshan Zhang
26
1,421
0
24 May 2019
Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using
  Non-IID Data
Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data
Naoya Yoshida
Takayuki Nishio
M. Morikura
Koji Yamamoto
Ryo Yonetani
32
137
0
17 May 2019
Incentive Design for Efficient Federated Learning in Mobile Networks: A
  Contract Theory Approach
Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach
Jiawen Kang
Zehui Xiong
Dusit Niyato
Han Yu
Ying-Chang Liang
Dong In Kim
FedML
34
212
0
16 May 2019
Client-Edge-Cloud Hierarchical Federated Learning
Client-Edge-Cloud Hierarchical Federated Learning
Lumin Liu
Jun Zhang
S. H. Song
Khaled B. Letaief
FedML
42
729
0
16 May 2019
Towards Federated Learning at Scale: System Design
Towards Federated Learning at Scale: System Design
Keith Bonawitz
Hubert Eichner
W. Grieskamp
Dzmitry Huba
A. Ingerman
...
H. B. McMahan
Timon Van Overveldt
David Petrou
Daniel Ramage
Jason Roselander
FedML
21
2,634
0
04 Feb 2019
Machine Learning at the Wireless Edge: Distributed Stochastic Gradient
  Descent Over-the-Air
Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air
Mohammad Mohammadi Amiri
Deniz Gunduz
30
53
0
03 Jan 2019
Wireless Network Intelligence at the Edge
Wireless Network Intelligence at the Edge
Jihong Park
S. Samarakoon
M. Bennis
Mérouane Debbah
21
518
0
07 Dec 2018
Communication-Efficient On-Device Machine Learning: Federated
  Distillation and Augmentation under Non-IID Private Data
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
Eunjeong Jeong
Seungeun Oh
Hyesung Kim
Jihong Park
M. Bennis
Seong-Lyun Kim
FedML
28
594
0
28 Nov 2018
Federated Learning for Keyword Spotting
Federated Learning for Keyword Spotting
David Leroy
A. Coucke
Thibaut Lavril
Thibault Gisselbrecht
Joseph Dureau
FedML
25
282
0
09 Oct 2018
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
1,688
0
14 Apr 2018
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