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Claire McKay Bowen
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Comparative study of differentially private data synthesis methods
CMK Bowen, F Liu
Statistical Science 35 (2), 280--307, 2020
98*2020
Comparative Study of Differentially Private Synthetic Data Algorithms from the NIST PSCR Differential Privacy Synthetic Data Challenge
CMK Bowen, J Snoke
Journal of Privacy and Confidentiality 11 (1), 2021
682021
Partitioning a large simulation as it runs
K Myers, E Lawrence, M Fugate, CMK Bowen, L Ticknor, J Woodring, ...
Technometrics 58 (3), 329-340, 2016
39*2016
A synthetic supplemental public use file of low-income information return data: methodology, utility, and privacy implications
CMK Bowen, V Bryant, L Burman, S Khitatrakun, R McClelland, ...
Privacy in Statistical Databases: UNESCO Chair in Data Privacy …, 2020
262020
A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data
AF Barrientos, AR Williams, J Snoke, CMK Bowen
Journal of the American Statistical Association 119 (545), 52-65, 2024
172024
Synthetic individual income tax data: promises and challenges
CMK Bowen, VL Bryant, L Burman, S Khitatrakun, R McClelland, ...
National Tax Journal 75 (4), 767-790, 2022
132022
Differentially Private Data Release via Statistical Election to Partition Sequentially
CMK Bowen, F Liu, B Su
METRON, 2021
13*2021
Synthetic individual income tax data: Methodology, utility, and privacy implications
CMK Bowen, V Bryant, L Burman, J Czajka, S Khitatrakun, G MacDonald, ...
International Conference on Privacy in Statistical Databases, 191-204, 2022
122022
Philosophy of differential privacy
CM Bowen, S Garfinkel
Notices of the American Mathematical Society 68 (10), 2021
122021
How statisticians should grapple with privacy in a changing data landscape
J Snoke, CMK Bowen
Chance 33 (4), 6-13, 2020
122020
The promise and limitations of formal privacy
AR Williams, CMK Bowen
Wiley Interdisciplinary Reviews: Computational Statistics, e1615, 2023
112023
A privacy-preserving validation server prototype
S Taylor, G MacDonald, K Ueyama, CMK Bowen
Technical Paper. Urban Institute, Washington, DC, 2021
112021
Differentially private generation of social networks via exponential random graph models
F Liu, E Eugenio, IH Jin, C Bowen
2020 IEEE 44th Annual Computers, Software, and Applications Conference …, 2020
82020
Disclosing Economists’ Privacy Perspectives: A Survey of American Economic Association Members’ Views on Differential Privacy and the Usability of Noise-Infused Data
AR Williams, J Snoke, CMK Bowen, AF Barrientos
Harvard Data Science Review, 2024
72024
Advancing microdata privacy protection: A review of synthetic data methods
J Hu, CMK Bowen
Wiley Interdisciplinary Reviews: Computational Statistics, e1636, 2024
7*2024
Incompatibilities between Current Practices in Statistical Data Analysis and Differential Privacy
J Snoke, CMK Bowen, AR Williams, AF Barrientos
arXiv preprint arXiv:2309.16703, 2023
62023
Do No Harm Guide: Applying Equity Awareness in Data Privacy Methods
C Bowen, J Snoke
< bound method Organization. get_name_with_acronym of< Organization: Urban …, 2023
62023
The art of data privacy
CMK Bowen
Significance 19 (1), 14-19, 2022
62022
Protecting your privacy in a data-driven world
CMK Bowen
Chapman and Hall/CRC, 2021
62021
Differentially private methods for validation servers
AF Barrientos, AR Williams, J Snoke, CM Bowen
Urban Institute research report, 2021
6*2021
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