Towards understanding quality challenges of the federated learning for neural networks: a first look from the lens of robustness

Federated learning (FL) is a distributed learning paradigm that preserves users’ data privacy while leveraging the entire dataset of all participants. In FL, multiple models are trained independently on the clients and aggregated centrally to update a global model in an iterative process. Although t...

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