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FEDEBA+: TOWARDS FAIR AND EFFECTIVE FEDERATED LEARNING VIA ENTROPY-BASED MODEL
Ensuring fairness is a crucial aspect of Federated Learning (FL), which enables the model to perform consistently across all clients. However, designing an FL algorithm that... -
A Fair Federated Learning Framework With Reinforcement Learning
Federated learning (FL) is a paradigm where many clients collaboratively train a model under the coordination of a central server, while keeping the training data locally...
