Abstract: Federated learning (FL) allows multiple clients to collectively train a high-performance global model without sharing their private data. However, the key challenge in federated learning is ...

Abstract: Supervised machine learning models are trained on historical data to learn a static mapping between their input and output variables. However, when they are deployed on continuously streamed ...

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