FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution
Graph Federated Learning (GFL) is an emerging distributed training paradigm that combines federated learning with graph data. Due to its ability to effectively handle complex and heterogeneous graph data while protecting user privacy, GFL has shown great potential in processing various types of grap...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10857280/ |
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