The Impact of Differential Privacy on Model Fairness in Federated Learning

Federated learning is a machine learning framework where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g. service provider), while keeping the training data decentral

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