Federated learning for graph neural networks

This dissertation investigates the combination of graph neural networks (GNNs) and federated learning (FL) for addressing practical problems while preserving data privacy and reducing computational complexity. Specifically, we reproduce the Graph Clustered Federated Learning (GCFL) framework and...

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Bibliographic Details
Main Author: Yan, Yige
Other Authors: Tay Wee Peng
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167083
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Institution: Nanyang Technological University
Language: English