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FedUV: Uniformity and Variance for Heterogeneous Federated Learning
Based on this finding, we introduce two regularization terms for local training to continuously emulate IID settings: (1) variance in the dimension-wise probability distribution of the classifier and (2) hyperspherical uniformity of representations of the encoder.
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