22 citations · 64 across the 12 of their papers we have counts for
5 papers · 1 filter
Classification Protocols with Minimal Disclosure
Jinshuo Dong, Jason Hartline, Aravindan Vijayaraghavan
We consider multi-party protocols for classification that are motivated by applications such as e-discovery in court proceedings. We identify a protocol that guarantees that the re…
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy
Jordan Awan, Jinshuo Dong
A canonical noise distribution (CND) is an additive mechanism designed to satisfy -differential privacy (-DP), without any wasted privacy budget. -DP is a hypothesis testi…
Privacy Amplification via Iteration for Shuffled and Online PNSGD
Matteo Sordello, Zhiqi Bu, Jinshuo Dong
In this paper, we consider the framework of privacy amplification via iteration, which is originally proposed by Feldman et al. and subsequently simplified by Asoodeh et al. in the…
Rejoinder: Gaussian Differential Privacy
Jinshuo Dong, Aaron Roth, Weijie J. Su
In this rejoinder, we aim to address two broad issues that cover most comments made in the discussion. First, we discuss some theoretical aspects of our work and comment on how thi…
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity
Jinshuo Dong, David Durfee, Ryan Rogers
Composition is one of the most important properties of differential privacy (DP), as it allows algorithm designers to build complex private algorithms from DP primitives. We consid…