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FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning
This paper introduces FedDistill, a framework enhancing the knowledge transfer from the global model to local models, focusing on the issue of imbalanced class distribution.
Quantum learning and essential cognition under the traction of meta-characteristics in an open world
This is because things in the new and old worlds have different units and dimensions for their features.
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