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Found 2 papers, 1 papers with code
Modeling Global Distribution for Federated Learning with Label Distribution Skew
It introduces a global Generative Adversarial Network to model the global data distribution without access to local datasets, so the global model can be trained using the global information of data distribution without privacy leakage.
Representation Learning of Knowledge Graph for Wireless Communication Networks
Finally, the results show that the classification accuracy of the proposed model is better than the existing unsupervised graph neural network models, such as VGAE and ARVGE.
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