most citedPrivacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

5 citations · 5 across the 1 of their papers we have counts for

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stat.ML2023★ 5 cited

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

Wei-Ning Chen, Dan Song, Ayfer Ozgur +1

Privacy and communication constraints are two major bottlenecks in federated learning (FL) and analytics (FA). We study the optimal accuracy of mean and frequency estimation (canon…