3 papers
cs.CR2026
A Sieve-Accelerated Quadrature Method for Exact Privacy Accounting in the 2020 U.S. Decennial Census
Buxin Su, Weijie Su, Chendi Wang
In 2020, the U.S. Census Bureau adopted differential privacy for the Decennial Census by injecting integer-valued Gaussian noise into published census tabulations. Exactly evaluati…
cs.CR2026
The 2020 US Decennial Census is more private than you (might) think
Buxin Su, Weijie J. Su, Chendi Wang
The U.S. Decennial Census serves as the foundation for many high-profile policy decision-making processes, including federal funding allocation and redistricting. In 2020, the Cens…
cs.LG2025
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via -Differential Privacy
Xiang Li, Buxin Su, Chendi Wang +2
Differentially private (DP) decentralized Federated Learning (FL) allows local users to collaborate without sharing their data with a central server. However, accurately quantifyin…