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cs.CV2025
VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis
Chia-Yi Hsu, Jia-You Chen, Yu-Lin Tsai +4
Differentially private (DP) synthetic data has become the de facto standard for releasing sensitive data. However, many DP generative models suffer from the low utility of syntheti…
cs.CV2023
DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase
Chih-Hsun Lin, Chia-Yi Hsu, Chia-Mu Yu +2
Differentially private synthetic data is a promising alternative for sensitive data release. Many differentially private generative models have been proposed in the literature. Unf…
cs.CV2018
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces
Chia-Yi Hsu, Pei-Hsuan Lu, Pin-Yu Chen +1
Recent studies have found that deep learning systems are vulnerable to adversarial examples; e.g., visually unrecognizable adversarial images can easily be crafted to result in mis…