activity
20232026
most citedOnline Differentially Private Synthetic Data Generation

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

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.…

math.ST2026

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…

math.PR2025

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 we d…

math.PR2024

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…

math.ST2024★ 1 cited

Online Differentially Private Synthetic Data Generation

Yiyun He, Roman Vershynin, Yizhe Zhu

We present a polynomial-time algorithm for online differentially private synthetic data generation. For a data stream within the hypercube and an infinite time horizon, w…

cs.LG2023★ 1 cited

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…