Data Augmentation

SOMA: A Novel Sampler for Bayesian Inference from Privatized Data

Making valid statistical inferences from privatized data is a key challenge in modern analysis. In Bayesian settings, data augmentation MCMC (DAMCMC) methods impute unobserved …

yifei-xiong

• May 1, 2025 • 1 min read

MCMC

Data Augmentation MCMC for Bayesian Inference from Privatized Data

Differentially private mechanisms protect privacy by introducing additional randomness into the data. Restricting access to only the privatized data makes it challenging to perform …

Nianqiao Phyllis Ju

• Jun 1, 2022 • 1 min read

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Data Augmentation

SOMA: A Novel Sampler for Bayesian Inference from Privatized Data

Data Augmentation MCMC for Bayesian Inference from Privatized Data