3 citations · 4 across the 3 of their papers we have counts for
4 papers
Robust Single-message Shuffle Differential Privacy Protocol for Accurate Distribution Estimation
Xiaoguang Li, Hanyi Wang, Yaowei Huang +6
Shuffler-based differential privacy (shuffle-DP) is a privacy paradigm providing high utility by involving a shuffler to permute noisy report from users. Existing shuffle-DP protoc…
Weights Shuffling for Improving DPSGD in Transformer-based Models
Jungang Yang, Zhe Ji, Liyao Xiang
Differential Privacy (DP) mechanisms, especially in high-dimensional settings, often face the challenge of maintaining privacy without compromising the data utility. This work intr…
Improved Matrix Gaussian Mechanism for Differential Privacy
Jungang Yang, Liyao Xiang, Weiting Li +2
The wide deployment of machine learning in recent years gives rise to a great demand for large-scale and high-dimensional data, for which the privacy raises serious concern. Differ…
Certified Distributional Robustness on Smoothed Classifiers
Jungang Yang, Liyao Xiang, Ruidong Chen +3
The robustness of deep neural networks (DNNs) against adversarial example attacks has raised wide attention. For smoothed classifiers, we propose the worst-case adversarial loss ov…