5 papers
Minimax optimal differentially private synthetic data for smooth queries
Rundong Ding, Yiyun He, Yizhe Zhu
Differentially private synthetic data enables the sharing and analysis of sensitive datasets while providing rigorous privacy guarantees for individual contributors. A central chal…
FL-Sailer: Efficient and Privacy-Preserving Federated Learning for Scalable Single-Cell Epigenetic Data Analysis via Adaptive Sampling
Guangyi Zhang, Yi Dai, Yiyun He +1
Single-cell ATAC-seq (scATAC-seq) enables high-resolution mapping of chromatin accessibility, yet privacy regulations and data size constraints hinder multi-institutional sharing.…
Sparse Hanson-Wright Inequalities with Applications
Yiyun He, Ke Wang, Yizhe Zhu
We derive new Hanson-Wright-type inequalities tailored to the quadratic forms of random vectors with sparse independent components. Specifically, we consider cases where the compon…
A note on the improved sparse Hanson-Wright inequalities
Guozheng Dai, Yiyun He, Ke Wang +1
We establish sparse Hanson-Wright inequalities for quadratic forms of sparse -sub-exponential random vectors with exponent parameter . In the regime w…
Differentially Private Low-dimensional Synthetic Data from High-dimensional Datasets
Yiyun He, Thomas Strohmer, Roman Vershynin +1
Differentially private synthetic data provide a powerful mechanism to enable data analysis while protecting sensitive information about individuals. However, when the data lie in a…