activity
20182021
most citedProving Differential Privacy with Shadow Execution

47 citations · 91 across the 5 of their papers we have counts for

collaborators

10 papers

cs.CR202110 cited

DPGen: Automated Program Synthesis for Differential Privacy

Yuxin Wang, Zeyu Ding, Yingtai Xiao +2

Differential privacy has become a de facto standard for releasing data in a privacy-preserving way. Creating a differentially private algorithm is a process that often starts with…

cs.CR2021

The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise

Zeyu Ding, Daniel Kifer, Sayed M. Saghaian N. E. +4

The permute-and-flip mechanism is a recently proposed differentially private selection algorithm that was shown to outperform the exponential mechanism. In this paper, we show that…

cs.DB2020

Free Gap Estimates from the Exponential Mechanism, Sparse Vector, Noisy Max and Related Algorithms

Zeyu Ding, Yuxin Wang, Yingtai Xiao +3

Private selection algorithms, such as the Exponential Mechanism, Noisy Max and Sparse Vector, are used to select items (such as queries with large answers) from a set of candidates…

cs.DB2020

Optimizing Fitness-For-Use of Differentially Private Linear Queries

Yingtai Xiao, Zeyu Ding, Yuxin Wang +2

In practice, differentially private data releases are designed to support a variety of applications. A data release is fit for use if it meets target accuracy requirements for each…

cs.PL202033 cited

CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples

Yuxin Wang, Zeyu Ding, Daniel Kifer +1

We propose CheckDP, the first automated and integrated approach for proving or disproving claims that a mechanism is differentially private. CheckDP can find counterexamples for me…

math.NT20191 cited

Canonical Barsotti-Tate Groups of Finite Level

Zeyu Ding

Let be an algebraically closed field of characteristic . Let be such that . Let be a -divisible group of codimension and dimension…