The paper introduces dpmm, an open-source library that implements three differentially private marginal models with end-to-end DP guarantees, improved utility on Wine, and built-in privacy auditing.
Data synthesis via differentially private markov random fields
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dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation
The paper introduces dpmm, an open-source library that implements three differentially private marginal models with end-to-end DP guarantees, improved utility on Wine, and built-in privacy auditing.