Instruction: Discuss strategies to achieve model convergence and address the challenge posed by non-IID data distributions in Federated Learning environments.
Context: This question assesses the candidate's understanding of the inherent challenges of non-IID data in Federated Learning and their ability to implement strategies that ensure model convergence despite these challenges.
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I would focus on both optimization and evaluation. On the optimization side, I would use methods that reduce client drift, control local step size, and possibly personalize or cluster clients when one global model is too blunt. On the evaluation...