Instruction: Discuss strategies to handle sparse data in Federated Learning, ensuring model performance is not compromised.
Context: Candidates must showcase their understanding of the challenges posed by sparse data in Federated Learning and propose effective strategies to overcome these challenges.
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The way I'd approach it in an interview is this: For sparse data scenarios, I would first check whether the sparsity is in features, labels, client participation, or all three, because the remedy depends on the source of sparsity. In many cases, strong initialization from pretraining, better client...