Aligning model outputs for class imbalanced non-IID federated learning

Federated Learning (FL) aims to generate a global shared model via collaborating with decentralized edge computing devices with privacy considerations. A significant challenge in FL is the non-IID data partitioning across heterogeneous devices, making the local update diverge a lot and difficult to...

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