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Resource-constrained Federated Edge Learning with Heterogeneous Data:
  Formulation and Analysis

Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis

14 October 2021
Yi Liu
Yuanshao Zhu
James J. Q. Yu
    FedML
ArXivPDFHTML

Papers citing "Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis"

13 / 13 papers shown
Title
A Comprehensive Survey on Joint Resource Allocation Strategies in
  Federated Edge Learning
A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning
Jingbo Zhang
Qiong Wu
Pingyi Fan
Q. Fan
FedML
28
0
0
10 Oct 2024
FedVAE: Trajectory privacy preserving based on Federated Variational
  AutoEncoder
FedVAE: Trajectory privacy preserving based on Federated Variational AutoEncoder
Yuchen Jiang
Ying Wu
Shiyao Zhang
J. J. Yu
25
3
0
12 Jul 2024
Training Machine Learning models at the Edge: A Survey
Training Machine Learning models at the Edge: A Survey
Aymen Rayane Khouas
Mohamed Reda Bouadjenek
Hakim Hacid
Sunil Aryal
29
10
0
05 Mar 2024
Temporal Gradient Inversion Attacks with Robust Optimization
Temporal Gradient Inversion Attacks with Robust Optimization
Bowen Li Jie Li
Hanlin Gu
Ruoxin Chen
Jie Li
Chentao Wu
Na Ruan
Xueming Si
Lixin Fan
AAML
33
2
0
13 Jun 2023
Hierarchical Personalized Federated Learning Over Massive Mobile Edge
  Computing Networks
Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks
Chaoqun You
Kun Guo
Howard H. Yang
Tony Q. S. Quek
38
16
0
19 Mar 2023
Need of 6G for the Metaverse Realization
Need of 6G for the Metaverse Realization
Bartlomiej Siniarski
C. D. Alwis
Gokul Yenduri
Thien Huynh-The
Gürkan Gür
Thippa Reddy Gadekallu
Madhusanka Liyanage
23
16
0
28 Dec 2022
Edge Learning for B5G Networks with Distributed Signal Processing:
  Semantic Communication, Edge Computing, and Wireless Sensing
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing
Wei Xu
Zhaohui Yang
Derrick Wing Kwan Ng
Marco Levorato
Yonina C. Eldar
Mérouane Debbah
28
398
0
01 Jun 2022
Enabling All In-Edge Deep Learning: A Literature Review
Enabling All In-Edge Deep Learning: A Literature Review
Praveen Joshi
Mohammed Hasanuzzaman
Chandra Thapa
Haithem Afli
T. Scully
21
22
0
07 Apr 2022
SHED: A Newton-type algorithm for federated learning based on
  incremental Hessian eigenvector sharing
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
Nicolò Dal Fabbro
S. Dey
M. Rossi
Luca Schenato
FedML
29
14
0
11 Feb 2022
Robust Semi-supervised Federated Learning for Images Automatic
  Recognition in Internet of Drones
Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones
Zhe Zhang
Shiyao Ma
Zhaohui Yang
Zehui Xiong
Jiawen Kang
Yi Wu
Kejia Zhang
Dusit Niyato
14
35
0
03 Jan 2022
Towards Communication-efficient and Attack-Resistant Federated Edge
  Learning for Industrial Internet of Things
Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Yi Liu
Ruihui Zhao
Jiawen Kang
A. Yassine
Dusit Niyato
Jia-Jie Peng
FedML
69
35
0
08 Dec 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
162
760
0
28 Sep 2019
Analyzing Federated Learning through an Adversarial Lens
Analyzing Federated Learning through an Adversarial Lens
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
S. Calo
FedML
179
1,032
0
29 Nov 2018
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