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Topology-aware Federated Learning in Edge Computing: A Comprehensive
  Survey

Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey

6 February 2023
Jiajun Wu
Steve Drew
Fan Dong
Zhuangdi Zhu
Jiayu Zhou
    FedML
ArXivPDFHTML

Papers citing "Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey"

10 / 10 papers shown
Title
Hubs and Spokes Learning: Efficient and Scalable Collaborative Machine Learning
Hubs and Spokes Learning: Efficient and Scalable Collaborative Machine Learning
Atul Sharma
Kavindu Herath
Saurabh Bagchi
Chaoyue Liu
Somali Chaterji
FedML
42
0
0
29 Apr 2025
Efficient Personalized Federated Learning via Sparse Model-Adaptation
Efficient Personalized Federated Learning via Sparse Model-Adaptation
Daoyuan Chen
Fandong Meng
Dawei Gao
Bolin Ding
Yaliang Li
FedML
108
47
0
04 May 2023
Decentralized Federated Learning: Fundamentals, State of the Art,
  Frameworks, Trends, and Challenges
Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges
Enrique Tomás Martínez Beltrán
Mario Quiles Pérez
Pedro Miguel Sánchez Sánchez
Sergio López Bernal
Gérome Bovet
M. Pérez
Gregorio Martínez Pérez
Alberto Huertas Celdrán
FedML
18
221
0
15 Nov 2022
Federated Learning Challenges and Opportunities: An Outlook
Federated Learning Challenges and Opportunities: An Outlook
Jie Ding
Eric W. Tramel
Anit Kumar Sahu
Shuang Wu
Salman Avestimehr
Tao Zhang
FedML
33
55
0
01 Feb 2022
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
840
0
01 Mar 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets
  with Ordered Dropout
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horváth
Stefanos Laskaridis
Mario Almeida
Ilias Leondiadis
Stylianos I. Venieris
Nicholas D. Lane
178
267
0
26 Feb 2021
Device Sampling for Heterogeneous Federated Learning: Theory,
  Algorithms, and Implementation
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
Su Wang
Mengyuan Lee
Seyyedali Hosseinalipour
Roberto Morabito
M. Chiang
Christopher G. Brinton
FedML
77
110
0
04 Jan 2021
Throughput-Optimal Topology Design for Cross-Silo Federated Learning
Throughput-Optimal Topology Design for Cross-Silo Federated Learning
Othmane Marfoq
Chuan Xu
Giovanni Neglia
Richard Vidal
FedML
62
85
0
23 Oct 2020
The Future of Digital Health with Federated Learning
The Future of Digital Health with Federated Learning
Nicola Rieke
Jonny Hancox
Wenqi Li
Fausto Milletari
H. Roth
...
Ronald M. Summers
Andrew Trask
Daguang Xu
Maximilian Baust
M. Jorge Cardoso
OOD
174
1,705
0
18 Mar 2020
FedPAQ: A Communication-Efficient Federated Learning Method with
  Periodic Averaging and Quantization
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh
Aryan Mokhtari
Hamed Hassani
Ali Jadbabaie
Ramtin Pedarsani
FedML
165
760
0
28 Sep 2019
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