51 citations · 348 across the 61 of their papers we have counts for
3 papers · 1 filter
On the Differential Privacy of Bayesian Inference
Zuhe Zhang, Benjamin Rubinstein, Christos Dimitrakakis
We study how to communicate findings of Bayesian inference to third parties, while preserving the strong guarantee of differential privacy. Our main contributions are four differen…
MOOCs Meet Measurement Theory: A Topic-Modelling Approach
Jiazhen He, Benjamin I. P. Rubinstein, James Bailey +3
This paper adapts topic models to the psychometric testing of MOOC students based on their online forum postings. Measurement theory from education and psychology provides statisti…
The Bernstein Mechanism: Function Release under Differential Privacy
Francesco Aldà, Benjamin I. P. Rubinstein
We address the problem of general function release under differential privacy, by developing a functional mechanism that applies under the weak assumptions of oracle access to targ…