PRIEST-KLD is a family of differentially private, communication-efficient estimators of KL divergence for federated data, with three trust models; however, the unbiasedness and privacy proofs have load-bearing gaps.
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Distributed, communication-efficient, and differentially private estimation of KL divergence
PRIEST-KLD is a family of differentially private, communication-efficient estimators of KL divergence for federated data, with three trust models; however, the unbiasedness and privacy proofs have load-bearing gaps.