Wanrong Zhang

According to our database, Wanrong Zhang authored at least 18 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Membership Inference Attacks and Privacy in Topic Modeling.

Nico Manzonelli, Wanrong Zhang, Salil P. Vadhan

CoRR, 2024

2023

Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control.

Wanrong Zhang, Yajun Mei

Technometrics, January, 2023

Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training.

Alyssa Huang, Peihan Liu, Ryumei Nakada, Linjun Zhang, Wanrong Zhang

CoRR, 2023

Continual Release of Differentially Private Synthetic Data.

Mark Bun, Marco Gaboardi, Marcel Neunhoeffer, Wanrong Zhang

CoRR, 2023

Challenges towards the Next Frontier in Privacy.

Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang

CoRR, 2023

Concurrent Composition Theorems for Differential Privacy.

Salil P. Vadhan, Wanrong Zhang

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference.

Wanrong Zhang, Ruqi Zhang

Proceedings of the International Conference on Machine Learning, 2023

Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters.

Samuel Haney, Michael Shoemate, Grace Tian, Salil P. Vadhan, Andrew Vyrros, Vicki Xu, Wanrong Zhang

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022

Concurrent Composition Theorems for all Standard Variants of Differential Privacy.

Salil P. Vadhan, Wanrong Zhang

CoRR, 2022

Attribute Privacy: Framework and Mechanisms.

Wanrong Zhang, Olga Ohrimenko, Rachel Cummings

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size.

Wanrong Zhang, Yajun Mei, Rachel Cummings

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Privacy-preserving Statistical Tools: Differential Privacy and Beyond.

Wanrong Zhang

PhD thesis, 2021

Single and Multiple Change-Point Detection with Differential Privacy.

Wanrong Zhang, Sara Krehbiel, Rui Tuo, Yajun Mei, Rachel Cummings

J. Mach. Learn. Res., 2021

Leakage of Dataset Properties in Multi-Party Machine Learning.

Wanrong Zhang, Shruti Tople, Olga Ohrimenko

Proceedings of the 30th USENIX Security Symposium, 2021

PAPRIKA: Private Online False Discovery Rate Control.

Wanrong Zhang, Gautam Kamath, Rachel Cummings

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Dataset-Level Attribute Leakage in Collaborative Learning.

Wanrong Zhang, Shruti Tople, Olga Ohrimenko

CoRR, 2020

Privately detecting changes in unknown distributions.

Rachel Cummings, Sara Krehbiel, Yuliia Lut, Wanrong Zhang

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Differentially Private Change-Point Detection.

Rachel Cummings, Sara Krehbiel, Yajun Mei, Rui Tuo, Wanrong Zhang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018