By averaging classifier weights per label across clients and tuning the central model on unlabeled data, federated learning can handle private, heterogeneous client label sets at accuracy close to the public-label setting.
Classification by pairwise coupling.Advances in neural information processing systems, 10, 1997
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Federated Learning with Heterogeneous and Private Label Sets
By averaging classifier weights per label across clients and tuning the central model on unlabeled data, federated learning can handle private, heterogeneous client label sets at accuracy close to the public-label setting.