Abstract: Federated Learning (FL) is to collaboratively train a global model among distributed clients by iteratively aggregating their local updates without sharing their raw data, whereby the global ...
Abstract: Due to the different acquisition conditions, large variations in the feature distributions of two temporal domains generally exist, known as temporal domain shift. The temporal domain shift ...
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