Wanrong Zhang

Orcid: 0000-0002-2393-2308

Affiliations:
  • Harvard University, MA, USA
  • Georgia Institute of Technology, School of Industrial and Systems Engineering, Atlanta, GA, USA (PhD 2021)


According to our database1, Wanrong Zhang authored at least 19 papers between 2018 and 2024.

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Timeline

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Bibliography

2024
Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections.
Proc. ACM Manag. Data, 2024

Membership Inference Attacks and Privacy in Topic Modeling.
CoRR, 2024

2023
Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control.
Technometrics, January, 2023

Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training.
CoRR, 2023

Continual Release of Differentially Private Synthetic Data.
CoRR, 2023

Challenges towards the Next Frontier in Privacy.
CoRR, 2023

Concurrent Composition Theorems for Differential Privacy.
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.
Proceedings of the International Conference on Machine Learning, 2023

Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022
Concurrent Composition Theorems for all Standard Variants of Differential Privacy.
CoRR, 2022

Attribute Privacy: Framework and Mechanisms.
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.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Privacy-preserving Statistical Tools: Differential Privacy and Beyond.
PhD thesis, 2021

Single and Multiple Change-Point Detection with Differential Privacy.
J. Mach. Learn. Res., 2021

Leakage of Dataset Properties in Multi-Party Machine Learning.
Proceedings of the 30th USENIX Security Symposium, 2021

PAPRIKA: Private Online False Discovery Rate Control.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Dataset-Level Attribute Leakage in Collaborative Learning.
CoRR, 2020

Privately detecting changes in unknown distributions.
Proceedings of the 37th International Conference on Machine Learning, 2020

2018
Differentially Private Change-Point Detection.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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