 Privacy without Noisy Gradients: Slicing Mechanism for Generative Model
TrainingNeural Information Processing Systems (NeurIPS), 2024 |
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 Post-processing Private Synthetic Data for Improving Utility on Selected
MeasuresNeural Information Processing Systems (NeurIPS), 2023 |
 PrivTrace: Differentially Private Trajectory Synthesis by Adaptive
Markov ModelUSENIX Security Symposium (USENIX Security), 2022 |
 Robin Hood and Matthew Effects: Differential Privacy Has Disparate
Impact on Synthetic DataInternational Conference on Machine Learning (ICML), 2021 |
 Winning the NIST Contest: A scalable and general approach to
differentially private synthetic dataJournal of Privacy and Confidentiality (JPC), 2021 |
 PrivSyn: Differentially Private Data Synthesis Zhikun Zhang Tianhao Wang Ninghui Li Jean Honorio Michael Backes Shibo He Jiming Chen Yang Zhang |
 Differentially Private Synthetic Medical Data Generation using
Convolutional GANsInformation Sciences (Inf. Sci.), 2020 |
