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Federated Graph Neural Networks: Overview, Techniques and Challenges

Federated Graph Neural Networks: Overview, Techniques and Challenges

15 February 2022
R. Liu
Pengwei Xing
Zichao Deng
Anran Li
Cuntai Guan
Han Yu
    FedML
ArXivPDFHTML

Papers citing "Federated Graph Neural Networks: Overview, Techniques and Challenges"

18 / 18 papers shown
Title
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
Zihan Chen
Xingbo Fu
Yushun Dong
Jundong Li
Cong Shen
FedML
64
0
0
29 Apr 2025
Subgraph Federated Learning for Local Generalization
Sungwon Kim
Yoonho Lee
Yunhak Oh
Namkyeong Lee
Sukwon Yun
Junseok Lee
Sein Kim
Carl Yang
Chanyoung Park
FedML
OOD
70
1
0
06 Mar 2025
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks
Pau Ferrer-Cid
Jose M. Barcelo-Ordinas
J. García-Vidal
37
2
0
28 Oct 2024
Backdoor Attack on Vertical Federated Graph Neural Network Learning
Backdoor Attack on Vertical Federated Graph Neural Network Learning
Jirui Yang
Peng Chen
Zhihui Lu
Ruijun Deng
Qiang Duan
Jianping Zeng
AAML
FedML
39
0
0
15 Oct 2024
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and
  Applications
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
Yi Zhang
Yuying Zhao
Zhaoqing Li
Xueqi Cheng
Yu-Chiang Frank Wang
Olivera Kotevska
Philip S. Yu
Tyler Derr
18
9
0
31 Aug 2023
Privacy-Preserving Graph Machine Learning from Data to Computation: A
  Survey
Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey
Dongqi Fu
Wenxuan Bao
Ross Maciejewski
Hanghang Tong
Jingrui He
18
8
0
10 Jul 2023
Heterogeneous Federated Learning on a Graph
Heterogeneous Federated Learning on a Graph
Huiyuan Wang
Xuyang Zhao
Weijie Lin
FedML
44
4
0
19 Sep 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang
Bang Wu
Xingliang Yuan
Shirui Pan
Hanghang Tong
Jian Pei
36
98
0
16 May 2022
Power Allocation for Wireless Federated Learning using Graph Neural
  Networks
Power Allocation for Wireless Federated Learning using Graph Neural Networks
Boning Li
A. Swami
Santiago Segarra
FedML
38
12
0
15 Nov 2021
STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural
  Networks
STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks
Guannan Lou
Yuze Liu
Tiehua Zhang
Xi Zheng
FedML
50
14
0
12 Nov 2021
FedMe: Federated Learning via Model Exchange
FedMe: Federated Learning via Model Exchange
Koji Matsuda
Yuya Sasaki
Chuan Xiao
Makoto Onizuka
FedML
29
14
0
15 Oct 2021
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based
  Vertical Federated Learning
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning
Jinyin Chen
Guohan Huang
Haibin Zheng
Shanqing Yu
Wenrong Jiang
Chen Cui
AAML
FedML
68
32
0
13 Oct 2021
A Graph Federated Architecture with Privacy Preserving Learning
A Graph Federated Architecture with Privacy Preserving Learning
Elsa Rizk
A. H. Sayed
FedML
26
21
0
26 Apr 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
177
832
0
01 Mar 2021
A New Look and Convergence Rate of Federated Multi-Task Learning with
  Laplacian Regularization
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization
Canh T. Dinh
Thanh Tung Vu
N. H. Tran
Minh N. Dao
Hongyu Zhang
FedML
57
38
0
14 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey
Explainability in Graph Neural Networks: A Taxonomic Survey
Hao Yuan
Haiyang Yu
Shurui Gui
Shuiwang Ji
159
463
0
31 Dec 2020
GraphFL: A Federated Learning Framework for Semi-Supervised Node
  Classification on Graphs
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Binghui Wang
Ang Li
H. Li
Yiran Chen
68
115
0
08 Dec 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
234
11,568
0
09 Mar 2017
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