Abstract: Federated learning is useful when predicting user preferences due to its ability to keep user data private. As such, certain data samples may be more useful than others. For instance, with a ...
Abstract: Federated learning (FL), as a distributed machine learning paradigm, enables multiple users to train machine learning models locally using individual data and then update global model in a ...
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