SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation-Reference-Cited by-同舟云学术

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SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation

Published:2024-05-20 Issue: Volume: Page:1141-1150
ISSN:
Container-title:IEEE INFOCOM 2024 - IEEE Conference on Computer Communications
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Author:

Zhong Luying¹,Pi Yueyang¹,Chen Zheyi¹,Yu Zhengxin²,Miao Wang³,Chen Xing¹,Min Geyong⁴

Affiliation:

1. Fuzhou University,College of Computer and Data Science,China

2. University of Lancaster,School of Computing and Communications,UK

3. University of Plymouth,School of Engineering, Computing and Mathematics,UK

4. University of Exeter,Department of Computer Science,UK

Funder

National Natural Science Foundation of China

Technology Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10621050/10621073/10621368.pdf?arnumber=10621368

Reference32 articles.

1. MalGraph: Hierarchical Graph Neural Networks for Robust Windows Malware Detection

2. Federated graph classification over non-iid graphs;Xie;Advances in Neural Information Processing Systems (NIPS),2021

3. Differentially Private Federated Knowledge Graphs Embedding

4. Graph-Fraudster: Adversarial Attacks on Graph Neural Network-Based Vertical Federated Learning

5. DeepTMA: Predicting Effective Contention Models for Network Calculus using Graph Neural Networks

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