791 citations · 1.8k across the 42 of their papers we have counts for
43 papers
Dynamic Question Ordering in Online Surveys
Kirstin Early, Jennifer Mankoff, Stephen E. Fienberg
Online surveys have the potential to support adaptive questions, where later questions depend on earlier responses. Past work has taken a rule-based approach, uniformly across all…
Differentially Private Model Selection with Penalized and Constrained Likelihood
Jing Lei, Anne-Sophie Charest, Aleksandra Slavkovic +2
In statistical disclosure control, the goal of data analysis is twofold: The released information must provide accurate and useful statistics about the underlying population of int…
On-Average KL-Privacy and its equivalence to Generalization for Max-Entropy Mechanisms
Yu-Xiang Wang, Jing Lei, Stephen E. Fienberg
We define On-Average KL-Privacy and present its properties and connections to differential privacy, generalization and information-theoretic quantities including max-information an…
A Minimax Theory for Adaptive Data Analysis
Yu-Xiang Wang, Jing Lei, Stephen E. Fienberg
In adaptive data analysis, the user makes a sequence of queries on the data, where at each step the choice of query may depend on the results in previous steps. The releases are of…
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Yu-Xiang Wang, Stephen E. Fienberg, Alex Smola
We consider the problem of Bayesian learning on sensitive datasets and present two simple but somewhat surprising results that connect Bayesian learning to "differential privacy:,…
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle
Yu-Xiang Wang, Jing Lei, Stephen E. Fienberg
While machine learning has proven to be a powerful data-driven solution to many real-life problems, its use in sensitive domains has been limited due to privacy concerns. A popular…