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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格式: | Thesis-Master by Coursework |
語言: | English |
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Nanyang Technological University
2023
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在線閱讀: | https://hdl.handle.net/10356/167083 |
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機構: | Nanyang Technological University |
語言: | English |