research
∙
07/28/2023
Mean Estimation with User-level Privacy under Data Heterogeneity
A key challenge in many modern data analysis tasks is that user data are...
share
research
∙
03/24/2023
Differentially Private Synthetic Control
Synthetic control is a causal inference tool used to estimate the treatm...
research
∙
03/01/2023
What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy
Differential privacy (DP) is a mathematical privacy notion increasingly ...
research
∙
02/02/2023
Robust Estimation under the Wasserstein Distance
We study the problem of robust distribution estimation under the Wassers...
research
∙
09/13/2022
Optimal Data Acquisition with Privacy-Aware Agents
We study the problem faced by a data analyst or platform that wishes to ...
research
∙
04/10/2022
Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size
The sequential hypothesis testing problem is a class of statistical anal...
research
∙
11/02/2021
Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis
The Wasserstein distance, rooted in optimal transport (OT) theory, is a ...
research
∙
10/13/2021
"I need a better description”: An Investigation Into User Expectations For Differential Privacy
Despite recent widespread deployment of differential privacy, relatively...
research
∙
08/15/2021
How we browse: Measurement and analysis of digital behavior
Accurately analyzing and modeling online browsing behavior play a key ro...
research
∙
03/25/2021
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation
Normalizing flow models have risen as a popular solution to the problem ...
research
∙
10/24/2020
Differentially Private Online Submodular Maximization
In this work we consider the problem of online submodular maximization u...
research
∙
09/08/2020
Attribute Privacy: Framework and Mechanisms
Ensuring the privacy of training data is a growing concern since many ma...
research
∙
03/20/2020
Locally Interpretable Predictions of Parkinson's Disease Progression
In precision medicine, machine learning techniques have been commonly pr...
research
∙
02/27/2020
PAPRIKA: Private Online False Discovery Rate Control
In hypothesis testing, a false discovery occurs when a hypothesis is inc...
research
∙
12/12/2019
Algorithmic Price Discrimination
We consider a generalization of the third degree price discrimination pr...
research
∙
12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
research
∙
12/06/2019
Differentially Private Mixed-Type Data Generation For Unsupervised Learning
In this work we introduce the DP-auto-GAN framework for synthetic data g...
research
∙
10/03/2019
Privately detecting changes in unknown distributions
The change-point detection problem seeks to identify distributional chan...
research
∙
08/29/2018
Differentially Private Change-Point Detection
The change-point detection problem seeks to identify distributional chan...
research
∙
07/06/2018
Differentially Private Online Submodular Optimization
In this paper we develop the first algorithms for online submodular mini...
research
∙
04/23/2018
Individual Sensitivity Preprocessing for Data Privacy
The sensitivity metric in differential privacy, which is informally defi...
research
∙
03/16/2018
Differential Privacy for Growing Databases
We study the design of differentially private algorithms for adaptive an...
research
∙
02/24/2016
The Possibilities and Limitations of Private Prediction Markets
We consider the design of private prediction markets, financial markets ...
research
∙
06/10/2015
