Synthetic data generation is a powerful tool for privacy protection when...
Probabilistic models such as logistic regression, Bayesian classificatio...
The large number of publicly available survey datasets of wide variety,
...
This paper introduces a new method that embeds any Bayesian model used t...
When releasing record-level data containing sensitive information to the...
Synthetic data is a promising approach to privacy protection in many
con...
Recent research in differential privacy demonstrated that (sub)sampling ...
We propose three synthetic microdata approaches to generate private tabu...
In many contexts, missing data and disclosure control are ubiquitous and...
We propose a two-phase synthesis process for synthesizing income, a sens...
We propose a general approach to evaluating identification risk of conti...
We implement a pseudo posterior synthesizer for microdata dissemination ...
Bayesian statistics has gained great momentum since the computational
de...
We propose a Bayesian pseudo posterior mechanism to generate record-leve...
High-utility and low-risks synthetic data facilitates microdata dissemin...
Statistical agencies utilize models to synthesize respondent-level data ...
The release of synthetic data generated from a model estimated on the da...
The synthetic data approach to data confidentiality has been actively
re...
In this paper we investigate if generating synthetic data can be a viabl...