1 citations · 1 across the 3 of their papers we have counts for
4 papers
On Inherent Privacy of Posterior Sampling: A Unified Rényi-Divergence Framework
Ruyu Zhou, Fang Liu
Differential Privacy (DP) provides a rigorous framework for quantifying privacy guarantees. While most methods achieve DP by injecting calibrated random noise, the intrinsic random…
PRECISE: PRivacy-loss-Efficient and Consistent Inference based on poSterior quantilEs
Ruyu Zhou, Fang Liu
Differential Privacy (DP) is a mathematical framework for releasing information with formal privacy guarantees. While numerous DP procedures have been developed for statistical ana…
Efficient approximation of Earth Mover's Distance Based on Nearest Neighbor Search
Guangyu Meng, Ruyu Zhou, Liu Liu +5
Earth Mover's Distance (EMD) is an important similarity measure between two distributions, used in computer vision and many other application domains. However, its exact calculatio…
Enhancing Trade-offs in Privacy, Utility, and Computational Efficiency through MUltistage Sampling Technique (MUST)
Xingyuan Zhao, Ruyu Zhou, Fang Liu
Applying a randomized algorithm to a subset rather than the entire dataset amplifies privacy guarantees. We propose a class of subsampling methods ``MUltistage Sampling Technique (…