Instruction: Describe metrics or methods for evaluating the performance and effectiveness of Federated Learning models deployed in practical applications.
Context: This question tests the candidate’s ability to apply theoretical knowledge to practical situations, emphasizing the evaluation of Federated Learning models in the real world.
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The way I'd approach it in an interview is this: I measure effectiveness using both model quality and system quality. Model-side metrics include global performance, client-level performance distribution, fairness across segments, and robustness under heterogeneous data. System-side metrics...