5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CR2023★ 1 cited
Federated Experiment Design under Distributed Differential Privacy
Wei-Ning Chen, Graham Cormode, Akash Bharadwaj +2
Experiment design has a rich history dating back over a century and has found many critical applications across various fields since then. The use and collection of users' data in…
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…
cs.CR2022
The Poisson binomial mechanism for secure and private federated learning
Wei-Ning Chen, Ayfer Özgür, Peter Kairouz
We introduce the Poisson Binomial mechanism (PBM), a discrete differential privacy mechanism for distributed mean estimation (DME) with applications to federated learning and analy…