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We present a method for producing unbiased parameter estimates and valid confidence intervals under the constraints of differential privacy, a formal framework for limiting individual information leakage from sensitive data.
The combination of estimates from different experiments
Cochran, W. G. (1954) · 1954
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Inadmissibility of the usual estimator for the mean of a multivariate normal distribution
Stein, C. (1956) · 1956
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On measures of entropy and information
Rényi, A. (1961) · 1961
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Estimation with quadratic loss
Stein, C. and James, W. (1961) · 1961
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Disclosure-limited data dissemination
Duncan, G. T. and Lambert, D. (1986) · 1986
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The risk of disclosure for microdata
Duncan, G. and Lambert, D. (1989) · 1989
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The causal effect of education on earnings
Card, D. (1999) · 1999
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Adaptive estimation of a quadratic functional by model selection
Laurent, B. and Massart, P. (2000) · 2000
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k-anonymity: A model for protecting privacy
Sweeney, L. (2002) · 2002
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Revealing information while preserving privacy
Dinur, I. and Nissim, K. (2003) · 2003
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Estimating risks of identification disclosure in microdata
Reiter, J. P. (2005) · 2005
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Calibrating noise to sensitivity in private data analysis
Dwork, C., McSherry, F., Nissim, K., and Smith, A. (2006) · 2006
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Differentially private simple linear regression
Alabi, D., McMillan, A., Sarathy, J., Smith, A., and Vadhan, S. (2020) · 2007
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t-closeness: Privacy beyond k-anonymity and l-diversity
Li, N., Li, T., and Venkatasubramanian, S. (2007) · 2007
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l-diversity: Privacy beyond k-anonymity
Machanavajjhala, A., Kifer, D., Gehrke, J., and Venkitasubramaniam, M. (2007) · 2007
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Smooth sensitivity and sampling in private data analysis
Nissim, K., Raskhodnikova, S., and Smith, A. (2007) · 2007
Cited alongside, same era.
Differential privacy and robust statistics
Dwork, C. and Lei, J. (2009) · 2009
Cited alongside, same era.
Differential privacy for clinical trial data: Preliminary evaluations
Vu, D. and Slavkovic, A. (2009) · 2009
Cited alongside, same era.
A statistical framework for differential privacy
Wasserman, L. and Zhou, S. (2010) · 2010
Cited alongside, same era.
The algorithmic foundations of differential privacy
Dwork, C. and Roth, A. (2014) · 2014
Cited alongside, same era.
A scalable bootstrap for massive data
Kleiner, A., Talwalkar, A., Sarkar, P., and Jordan, M. I. (2014) · 2014
Cited alongside, same era.
Revisiting differentially private linear regression: optimal and adaptive prediction & estimation in unbounded domain
Wang, Y.-X. (2018) · 2018
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Differentially private inference for binomial data
Awan, J. and Slavkovic, A. (2019) · 2019
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Differentially private significance tests for regression coefficients
Barrientos, A. F., Reiter, J. P., Machanavajjhala, A., and Chen, Y. (2019) · 2019
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The structure of optimal private tests for simple hypotheses
Canonne, C. L., Kamath, G., McMillan, A., Smith, A., and Ullman, J. (2019) · 2019
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Statistically valid inferences from privacy protected data
Evans, G., King, G., Schwenzfeier, M., and Thakurta, A. (2019) · 2019
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Differentially private confidence intervals for empirical risk minimization
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Differential privacy for social science inference
D’Orazio, V., Honaker, J., and King, G. (2015) · 2015
Cited alongside, same era.
Revisiting differentially private hypothesis tests for categorical data
Wang, Y., Lee, J., and Kifer, D. (2015) · 2015
Cited alongside, same era.
Sharp nonasymptotic bounds on the norm of random matrices with independent entries
Bandeira, A. S. and Van Handel, R. (2016) · 2016
Cited alongside, same era.
Concentrated differential privacy: Simplifications, extensions, and lower bounds
Bun, M. and Steinke, T. (2016) · 2016
Cited alongside, same era.
Differentially private chi-squared hypothesis testing: Goodness of fit and independence testing
Gaboardi, M., Lim, H., Rogers, R., and Vadhan, S. (2016) · 2016
Cited alongside, same era.
Differentially private model selection with penalized and constrained likelihood
Lei, J., Charest, A.-S., Slavkovic, A., Smith, A., and Fienberg, S. (2016) · 2016
Cited alongside, same era.
Wang, Y., Kifer, D., and Lee, J. (2019) · 2019
Later among the works it cites.
Coinpress: Practical private mean and covariance estimation
Biswas, S., Dong, Y., Kamath, G., and Ullman, J. (2020) · 2020
Later among the works it cites.
Differentially private confidence intervals
Du, W., Foot, C., Moniot, M., Bray, A., and Groce, A. (2020) · 2020
Later among the works it cites.
Sub‐weibull distributions: Generalizing sub‐gaussian and sub‐exponential properties to heavier tailed distributions
Vladimirova, M., Girard, S., Nguyen, H., and Arbel, J. (2020) · 2020
Later among the works it cites.
Differentially private inference via noisy optimization
Avella-Medina, M., Bradshaw, C., and Loh, P.-L. (2021) · 2021
Closest in time.
A feasibility study of differentially private summary statistics and regression analyses for administrative tax data
Barrientos, A. F., Williams, A. R., Snoke, J., and Bowen, C. M. (2021) · 2021
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Non-parametric differentially private confidence intervals for the median
Drechsler, J., Globus-Harris, I., McMillan, A., Sarathy, J., and Smith, A. D. (2021) · 2021
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Parametric bootstrap for differentially private confidence intervals
Ferrando, C., Wang, S., and Sheldon, D. (2021) · 2021
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Differentially private methods for managing model uncertainty in linear regression models
Peña, V. and Barrientos, A. F. (2021) · 2021
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Ipums usa: Version 11.0 [dataset]
Ruggles, S., Flood, S., Foster, S., Goeken, R., Pacas, J., Schouweiler, M., and Sobek, M. (2021) · 2021
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