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By Author
Search Results
Practical Data Synthesis for Large Samples
Gillian M Raab, Beata Nowok, Chris Dibben
67-97
On Regression-Tree-Based Synthetic Data Methods for Business Data
Joo Ho Lee, In Yong Kim, Christine M. O'Keefe
A New Data Collection Technique for Preserving Privacy
Samuel S Wu, Shigang Chen, Deborah L Burr, Long Zhang
99-129
Noise Multiplication for Statistical Disclosure Control of Extreme Values in Log-normal Regression Samples
Martin Klein, Thomas Mathew, Bimal Sinha
Multiple Imputation for Disclosure Limitation: Future Research Challenges
Jerome P. Reiter
Bayesian Estimation of Disclosure Risks for Multiply Imputed, Synthetic Data
Jerome P. Reiter, Quanli Wang, Biyuan Zhang
Statistical Disclosure Limitation: New Directions and Challenges
Natalie Shlomo
Model Selection when multiple imputation is used to protect confidentiality in public use data
Satkartar K. Kinney, Jerome P. Reiter, James O. Berger
A Privacy Preserving Algorithm to Release Sparse High-dimensional Histograms
Bai Li, Vishesh Karwa, Aleksandra Slavković, Rebecca Carter Steorts
Towards Providing Automated Feedback on the Quality of Inferences from Synthetic Datasets
David R. McClure, Jerome P. Reiter
Towards a Systematic Analysis of Privacy Definitions
Bing-Rong Lin, Dan Kifer
How Will Statistical Agencies Operate When All Data Are Private?
John M Abowd
Estimation of Regression Parameters from Noise Multiplied Data
Yan-Xia Lin, Phillip Wise
Releasing Microdata: Disclosure Risk Estimation, Data Masking and Assessing Utility
Natalie Shlomo
Privacy Protection from Sampling and Perturbation in Survey Microdata
Natalie Shlomo, Chris J. Skinner
Partial Information Releases for Confidential Contingency Table Entries: Present and Future Research Efforts
Aleksandra B. Slavkovic
An Axiomatic View of Statistical Privacy and Utility
Daniel Kifer, Bing-Rong Lin
Synthetic Business Microdata
an Australian example
Chien-Hung Chien, Alan Hepburn Welsh, John D Moore
1 - 18 of 18 items