Wanrong Zhang
Wanrong Zhang
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Leakage of dataset properties in {Multi-Party} machine learning
W Zhang, S Tople, O Ohrimenko
30th USENIX security symposium (USENIX Security 21), 2687-2704, 2021
Differentially private change-point detection
R Cummings, S Krehbiel, Y Mei, R Tuo, W Zhang
Advances in Neural Information Processing Systems, 10825-10834, 2018
Attribute privacy: Framework and mechanisms
W Zhang, O Ohrimenko, R Cummings
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
Bandit change-point detection for real-time monitoring high-dimensional data under sampling control
W Zhang, Y Mei
Technometrics 65 (1), 33-43, 2023
Challenges towards the Next Frontier in Privacy
R Cummings, D Desfontaines, D Evans, R Geambasu, M Jagielski, ...
arXiv preprint arXiv:2304.06929, 2023
Concurrent Composition Theorems for Differential Privacy
S Vadhan, W Zhang
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 507–519, 2023
Privately detecting changes in unknown distributions
R Cummings, S Krehbiel, Y Lut, W Zhang
International Conference on Machine Learning, 2227-2237, 2020
PAPRIKA: Private Online False Discovery Rate Control
W Zhang, G Kamath, R Cummings
Proceedings of the 38th International Conference on Machine Learning 139 …, 2020
Single and multiple change-point detection with differential privacy
W Zhang, S Krehbiel, R Tuo, Y Mei, R Cummings
The Journal of Machine Learning Research 22 (1), 1359-1394, 2021
Advancing differential privacy: Where we are now and future directions for real-world deployment
R Cummings, D Desfontaines, D Evans, R Geambasu, Y Huang, ...
PubPub 6 (1), 2024
DP-Fast MH: Private, fast, and accurate Metropolis-Hastings for large-scale Bayesian inference
W Zhang, R Zhang
International Conference on Machine Learning, 41847-41860, 2023
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
A Huang, P Liu, R Nakada, L Zhang, W Zhang
arXiv preprint arXiv:2306.08173, 2023
Training Private and Efficient Language Models with Synthetic Data from LLMs
D Yu, A Backurs, S Gopi, H Inan, J Kulkarni, Z Lin, C Xie, H Zhang, ...
Socially Responsible Language Modelling Research, 2023
A standardised differential privacy framework for epidemiological modeling with mobile phone data
MK Savi, A Yadav, W Zhang, N Vembar, A Schroeder, S Balsari, ...
PLOS Digital Health 2 (10), e0000233, 2023
Concurrent composition for interactive differential privacy with adaptive Privacy-Loss parameters
S Haney, M Shoemate, G Tian, S Vadhan, A Vyrros, V Xu, W Zhang
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications …, 2023
Continual Release of Differentially Private Synthetic Data
M Bun, M Gaboardi, M Neunhoeffer, W Zhang
arXiv preprint arXiv:2306.07884, 2023
Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size
W Zhang, Y Mei, R Cummings
International Conference on Artificial Intelligence and Statistics, 11356-11373, 2022
Privacy-preserving Statistical Tools: Differential Privacy and Beyond
W Zhang
Georgia Institute of Technology, 2021
Membership Inference Attacks and Privacy in Topic Modeling
N Manzonelli, W Zhang, S Vadhan
arXiv preprint arXiv:2403.04451, 2024
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