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Protecting the anonymity of online users through Bayesian data synthesis.

, , , and . Expert Syst. Appl., (April 2023)

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Protecting the anonymity of online users through Bayesian data synthesis., , , and . Expert Syst. Appl., (April 2023)The Quasi-Multinomial Synthesizer for Categorical Data., and . PSD, volume 11126 of Lecture Notes in Computer Science, page 75-91. Springer, (2018)Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications., , , , , , and . CoRR, (2022)Bayesian Estimation of Attribute and Identification Disclosure Risks in Synthetic Data.. Trans. Data Priv., 12 (1): 61-89 (2019)Accuracy Gains from Privacy Amplification Through Sampling for Differential Privacy., , and . CoRR, (2021)Disclosure Risk Evaluation for Fully Synthetic Categorical Data., , and . Privacy in Statistical Databases, volume 8744 of Lecture Notes in Computer Science, page 185-199. Springer, (2014)Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy., , and . J. Mach. Learn. Res., (2022)Identification Risks Evaluation of Partially Synthetic Data with the IdentificationRiskCalculation R Package., and . Trans. Data Priv., 14 (1): 37-52 (2021)Bayesian Data Synthesis and Disclosure Risk Quantification: An Application to the Consumer Expenditure Surveys., and . Trans. Data Priv., 16 (2): 83-121 (May 2023)Loss of Regularity of Solutions of the Lighthill Problem for Shock Diffraction for Potential Flow., , , and . SIAM J. Math. Anal., 52 (2): 1096-1114 (2020)