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ORCIDJerome P. Reiter
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- affiliation: Duke University, Durham, USA
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Journal Articles
- 2023
[j26]Olivier Binette
, Jerome P. Reiter:
ER-Evaluation: End-to-End Evaluation of Entity Resolution Systems. J. Open Source Softw. 8(92): 5619 (2023)- [j25]Jerome P. Reiter:
Synthetic Data: A Look Back and A Look Forward. Trans. Data Priv. 16(1): 15-24 (2023) - 2022
- [j24]Michelle Nixon, Andrés F. Barrientos, Jerome P. Reiter, Aleksandra B. Slavkovic:
A Latent Class Modeling Approach for Differentially Private Synthetic Data for Contingency Tables. J. Priv. Confidentiality 12(1) (2022) - 2021
- [j23]Ziang Wang, Jerome P. Reiter:
Post-processing Differentially Private Counts to Satisfy Additive Constraints. Trans. Data Priv. 14(2): 65-77 (2021) - 2018
- [j22]Gilad Amitai, Jerome P. Reiter:
Differentially private posterior summaries for linear regression coefficients. J. Priv. Confidentiality 8(1) (2018) - [j21]Jerome P. Reiter:
Reminiscences of Steve Fienberg. J. Priv. Confidentiality 8(1) (2018) - [j20]Yan Chen, Andrés F. Barrientos, Ashwin Machanavajjhala, Jerome P. Reiter:
Is my model any good: differentially private regression diagnostics. Knowl. Inf. Syst. 54(1): 33-64 (2018) - [j19]Haoyang Yu, Jerome P. Reiter:
Differentially Private Verification of Regression Predictions from Synthetic Data. Trans. Data Priv. 11(3): 279-297 (2018) - 2014
- [j18]Jerome P. Reiter, Quanli Wang, Biyuan Zhang:
Bayesian Estimation of Disclosure Risks for Multiply Imputed, Synthetic Data. J. Priv. Confidentiality 6(1) (2014) - 2013
- [j17]Joyee Ghosh, Jerome P. Reiter:
Secure Bayesian model averaging for horizontally partitioned data. Stat. Comput. 23(3): 311-322 (2013) - 2012
- [j16]Ashwin Machanavajjhala, Jerome P. Reiter:
Big privacy: protecting confidentiality in big data. XRDS 19(1): 20-23 (2012) - [j15]David McClure, Jerome P. Reiter:
Towards Providing Automated Feedback on the Quality of Inferences from Synthetic Datasets. J. Priv. Confidentiality 4(1) (2012) - [j14]David McClure, Jerome P. Reiter:
Differential Privacy and Statistical Disclosure Risk Measures: An Investigation with Binary Synthetic Data. Trans. Data Priv. 5(3): 535-552 (2012) - 2011
- [j13]Jörg Drechsler, Jerome P. Reiter:
An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets. Comput. Stat. Data Anal. 55(12): 3232-3243 (2011) - [j12]Satkartar K. Kinney, Jerome P. Reiter, James O. Berger:
Model Selection when multiple imputation is used to protect confidentiality in public use data. J. Priv. Confidentiality 2(2) (2011) - [j11]Jerome P. Reiter:
Comment on Article by Gates. J. Priv. Confidentiality 3(2) (2011) - 2010
- [j10]Jerome P. Reiter:
Multiple Imputation for Disclosure Limitation: Future Research Challenges. J. Priv. Confidentiality 1(2) (2010) - [j9]Gregory Caiola, Jerome P. Reiter:
Random Forests for Generating Partially Synthetic, Categorical Data. Trans. Data Priv. 3(1): 27-42 (2010) - 2009
- [j8]Jerome P. Reiter, Anna Oganian, Alan F. Karr:
Verification servers: Enabling analysts to assess the quality of inferences from public use data. Comput. Stat. Data Anal. 53(4): 1475-1482 (2009) - [j7]Jerome P. Reiter, Robin Mitra:
Estimating Risks of Identification Disclosure in Partially Synthetic Data. J. Priv. Confidentiality 1(1) (2009) - [j6]Mi-Ja Woo, Jerome P. Reiter, Anna Oganian, Alan F. Karr:
Global Measures of Data Utility for Microdata Masked for Disclosure Limitation. J. Priv. Confidentiality 1(1) (2009) - 2007
- [j5]Joyee Ghosh, Jerome P. Reiter, Alan F. Karr:
Secure computation with horizontally partitioned data using adaptive regression splines. Comput. Stat. Data Anal. 51(12): 5813-5820 (2007) - [j4]Alan F. Karr, William J. Fulp, Francisco Vera, S. Stanley Young, Xiaodong Lin, Jerome P. Reiter:
Secure, Privacy-Preserving Analysis of Distributed Databases. Technometrics 49(3): 335-345 (2007) - 2005
- [j3]Alan F. Karr, Jun Feng, Xiaodong Lin, Ashish P. Sanil, S. Stanley Young, Jerome P. Reiter:
Secure analysis of distributed chemical databases without data integration. J. Comput. Aided Mol. Des. 19(9-10): 739-747 (2005) - 2003
- [j2]Jerome P. Reiter:
Model Diagnostics for Remote Access Regression Servers. Stat. Comput. 13(4): 371-380 (2003) - 2000
- [j1]Jerome P. Reiter:
Using Statistics to Determine Causal Relationships. Am. Math. Mon. 107(1): 24-32 (2000)
Conference and Workshop Papers
- 2020
- [c7]Jiurui Tang, Jerome P. Reiter, Rebecca C. Steorts:
Bayesian Modeling for Simultaneous Regression and Record Linkage. PSD 2020: 209-223 - 2016
- [c6]Yan Chen, Ashwin Machanavajjhala, Jerome P. Reiter, Andrés F. Barrientos:
Differentially Private Regression Diagnostics. ICDM 2016: 81-90 - 2014
- [c5]Jingchen Hu, Jerome P. Reiter, Quanli Wang:
Disclosure Risk Evaluation for Fully Synthetic Categorical Data. Privacy in Statistical Databases 2014: 185-199 - 2008
- [c4]Jörg Drechsler, Jerome P. Reiter:
Accounting for Intruder Uncertainty Due to Sampling When Estimating Identification Disclosure Risks in Partially Synthetic Data. Privacy in Statistical Databases 2008: 227-238 - 2006
- [c3]Robin Mitra, Jerome P. Reiter:
Adjusting Survey Weights When Altering Identifying Design Variables Via Synthetic Data. Privacy in Statistical Databases 2006: 177-188 - 2004
- [c2]Alan F. Karr, Xiaodong Lin, Ashish P. Sanil, Jerome P. Reiter:
Regression on Distributed Databases via Secure Multi-Party Computation. DG.O 2004 - [c1]Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerome P. Reiter:
Privacy preserving regression modelling via distributed computation. KDD 2004: 677-682
Reference Works
- 2011
- [r1]Jerome P. Reiter:
Statistical Approaches to Protecting Confidentiality in Public Use Data. International Encyclopedia of Statistical Science 2011: 1386-1388
Informal and Other Publications
- 2024
- [i7]Tong Lin, Jerome P. Reiter:
Differentially Private Verification of Survey-Weighted Estimates. CoRR abs/2404.02519 (2024) - [i6]Olivier Binette, Youngsoo Baek, Siddharth Engineer, Christina Jones, Abel Dasylva, Jerome P. Reiter:
How to Evaluate Entity Resolution Systems: An Entity-Centric Framework with Application to Inventor Name Disambiguation. CoRR abs/2404.05622 (2024) - [i5]Zeki Kazan, Jerome P. Reiter:
Bayesian Inference Under Differential Privacy: Prior Selection Considerations with Application to Univariate Gaussian Data and Regression. CoRR abs/2405.13801 (2024) - [i4]Olivier Binette, Jerome P. Reiter:
Improving the Validity and Practical Usefulness of AI/ML Evaluations Using an Estimands Framework. CoRR abs/2406.10366 (2024) - 2023
- [i3]Zeki Kazan, Jerome P. Reiter:
Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy. CoRR abs/2306.13214 (2023) - [i2]Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael B. Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian M. Schmutte, Victoria A. Velkoff, Pavel Zhuravlev:
An In-Depth Examination of Requirements for Disclosure Risk Assessment. CoRR abs/2310.09398 (2023) - 2017
- [i1]John M. Abowd, Lorenzo Alvisi, Cynthia Dwork, Sampath Kannan, Ashwin Machanavajjhala, Jerome P. Reiter:
Privacy-Preserving Data Analysis for the Federal Statistical Agencies. CoRR abs/1701.00752 (2017)
Coauthor Index
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