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Showing 1 to 1 of 1 for “"Federated Domain Generalization"”.

  1. Federated Learning With Generalization To New Domains

    Federated Learning (FL) is an area of research that focuses on training machine learning models in a decentralized fashion without having the need to store all data on one central server. In this thesis, we address the challenges of data heterogeneity and label scarcity in FL by proposing two novel …

    queens Repository record for Federated Learning With Generalization To New Domains (opens in a new tab)