Explain the significance of hyperparameter tuning in Federated Learning and strategies for effective tuning.
Instruction: Discuss the role of hyperparameter tuning in Federated Learning and outline approaches for optimizing hyperparameters in a distributed learning environment.
Context: This question explores the candidate's knowledge of hyperparameter optimization in the context of Federated Learning, highlighting their strategies for achieving optimal model performance.
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Hyperparameter tuning matters even more in federated learning than in centralized training because parameters like local epoch count, client fraction, learning...