research
∙
09/17/2023
A Unifying Privacy Analysis Framework for Unknown Domain Algorithms in Differential Privacy
There are many existing differentially private algorithms for releasing ...
share
research
∙
06/24/2023
Adaptive Privacy Composition for Accuracy-first Mechanisms
In many practical applications of differential privacy, practitioners se...
research
∙
08/17/2022
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach
We study a new privacy model where users belong to certain sensitive gro...
research
∙
06/15/2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints
There is a disconnect between how researchers and practitioners handle p...
research
∙
03/10/2022
Fully Adaptive Composition in Differential Privacy
Composition is a key feature of differential privacy. Well-known advance...
research
∙
03/31/2021
Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown
We generalize the continuous observation privacy setting from Dwork et a...
research
∙
10/27/2020
A Members First Approach to Enabling LinkedIn's Labor Market Insights at Scale
We describe the privatization method used in reporting labor market insi...
research
∙
04/15/2020
Unifying Privacy Loss Composition for Data Analytics
Differential privacy (DP) provides rigorous privacy guarantees on indivi...
research
∙
02/14/2020
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale
We present a privacy system that leverages differential privacy to prote...
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
∙
06/21/2019
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
We design a general framework for answering adaptive statistical queries...
research
∙
05/10/2019
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition
We study the problem of top-k selection over a large domain universe sub...
research
∙
02/01/2019
Lower Bounds for Locally Private Estimation via Communication Complexity
We develop lower bounds for estimation under local privacy constraints--...
research
∙
12/03/2018
Protection Against Reconstruction and Its Applications in Private Federated Learning
Federated learning has become an exciting direction for both research an...
research
∙
10/18/2018
