FedOBP introduces a quantile-thresholded importance score based on a federated first-order Taylor approximation to select a small set of parameters for personalization, claiming better performance than prior PFL methods.
Metafed: Federated learning among federations with cyclic knowl- edge distillation for personalized healthcare,
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FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling
FedOBP introduces a quantile-thresholded importance score based on a federated first-order Taylor approximation to select a small set of parameters for personalization, claiming better performance than prior PFL methods.