Making the Most of Parallel Composition in Differential Privacy

19 September 2021

Papers citing "Making the Most of Parallel Composition in Differential Privacy"

8 / 8 papers shown

Title
The 2020 United States Decennial Census Is More Private Than You (Might) Think Buxin Su Weijie J. Su Chendi Wang 31 3 0 11 Oct 2024
Practical, Private Assurance of the Value of Collaboration H. Asghar Zhigang Lu Zhongrui Zhao Dali Kaafar FedML 24 0 0 04 Oct 2023
Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning Parham Gohari Matthew T. Hale Ufuk Topcu OffRL 30 1 0 13 Sep 2023
Turbo: Effective Caching in Differentially-Private Databases Kelly Kostopoulou Pierre Tholoniat Asaf Cidon Roxana Geambasu Mathias Lécuyer 18 1 0 28 Jun 2023
Practical Differentially Private Hyperparameter Tuning with Subsampling A. Koskela Tejas D. Kulkarni 36 14 0 27 Jan 2023
Cohere: Managing Differential Privacy in Large Scale Systems Nicolas Küchler Emanuel Opel Hidde Lycklama Alexander Viand Anwar Hithnawi 33 4 0 20 Jan 2023
On the Choice of Databases in Differential Privacy Composition Valentin Hartmann Vincent Bindschaedler Robert West 22 0 0 27 Sep 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 17 13 0 22 Feb 2022