46 citations
- U.S. National Science FoundationUS7 papers
- Vassar CollegeUS5 papers
- National Center for Science and Engineering StatisticsUS3 papers
- Amherst CollegeUS1 paper
- Educational Testing ServiceUS1 paper
- National University of SingaporeSG1 paper
- RTI InternationalUS1 paper
- University of California, Santa CruzUS1 paper
- University of IowaUS1 paper
- Western UniversityCA1 paper
Showing 2019 · stat.MEShow all
2 papers · 2 filters
stat.ME2019★ 8 cited
Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy
Terrance D. Savitsky, Matthew R. Williams, Jingchen Hu
We propose a Bayesian pseudo posterior mechanism to generate record-level synthetic databases equipped with an probabilistic differential privacy (pDP) guarantee, where $δ…
stat.ME2019★ 12 cited
Risk-Efficient Bayesian Data Synthesis for Privacy Protection
Jingchen Hu, Terrance D. Savitsky, Matthew R. Williams
Statistical agencies utilize models to synthesize respondent-level data for release to the public for privacy protection. In this work, we efficiently induce privacy protection int…