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Federated learning (FL) provides a communication-efficient approach to solve machine learning problems concerning distributed data, without sending raw data to a central server.
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Client selection for federated learning with heterogeneous resources in mobile edge
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Federated learning with non-iid data
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Adaptive federated learning in resource constrained edge computing systems
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