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• Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation

  Federated learning (FL) enables training of shared models across distributed edge devices while keeping raw data on-device.

• FedMargin - Federated Learning via Attentive Margin of Semantic Feature Representations

  Let’s play a simple game. Open the photo gallery on your phone and briefly scroll your images, do you see some patterns and recognize the objects you like on the images?

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