research
∙
09/06/2022
Classification Protocols with Minimal Disclosure
We consider multi-party protocols for classification that are motivated ...
share
research
∙
06/09/2022
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy
A canonical noise distribution (CND) is an additive mechanism designed t...
research
∙
06/20/2021
Privacy Amplification via Iteration for Shuffled and Online PNSGD
In this paper, we consider the framework of privacy amplification via it...
research
∙
06/16/2021
Optimal Accounting of Differential Privacy via Characteristic Function
Characterizing the privacy degradation over compositions, i.e., privacy ...
research
∙
04/05/2021
Rejoinder: Gaussian Differential Privacy
In this rejoinder, we aim to address two broad issues that cover most co...
research
∙
03/15/2021
A Central Limit Theorem for Differentially Private Query Answering
Perhaps the single most important use case for differential privacy is t...
research
∙
03/10/2020
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
Datasets containing sensitive information are often sequentially analyze...
research
∙
11/26/2019
Deep Learning with Gaussian Differential Privacy
Deep learning models are often trained on datasets that contain sensitiv...
research
∙
09/30/2019
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity
Composition is one of the most important properties of differential priv...
research
∙
05/22/2019
Equilibrium Characterization for Data Acquisition Games
We study a game between two firms in which each provide a service based ...
research
∙
05/07/2019
Gaussian Differential Privacy
Differential privacy has seen remarkable success as a rigorous and pract...
research
∙
10/22/2017
