What are the challenges and solutions for data validation in Federated Learning?

Instruction: Discuss the unique challenges of validating data quality in a Federated Learning context and propose solutions.

Context: This question evaluates the candidate's ability to ensure data integrity and quality in decentralized learning environments, a crucial aspect of successful Federated Learning implementations.

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The way I'd explain it in an interview is this: Data validation is difficult because you cannot inspect client data centrally in the same way you would in a standard pipeline. That makes it harder to detect corrupted inputs, schema issues, poisoning,...

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