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07/16/2023
MargCTGAN: A "Marginally” Better CTGAN for the Low Sample Regime
The potential of realistic and useful synthetic data is significant. How...
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02/15/2023
Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy
In recent years, diffusion models have achieved tremendous success in th...
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02/02/2023
Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy
This work proposes Fed-GLOSS-DP, a novel approach to privacy-preserving ...
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11/07/2022
Private Set Generation with Discriminative Information
Differentially private data generation techniques have become a promisin...
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07/12/2022
RelaxLoss: Defending Membership Inference Attacks without Losing Utility
As a long-term threat to the privacy of training data, membership infere...
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12/16/2020
Responsible Disclosure of Generative Models Using Scalable Fingerprinting
Over the past six years, deep generative models have achieved a qualitat...
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06/15/2020
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators
The wide-spread availability of rich data has fueled the growth of machi...
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09/09/2019
