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We consider the problem of differentially private selection.
Rules for ordering uncertain prospects
J. Hadar and W. R. Russell · 1969
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Mechanism design via differential privacy
F. McSherry and K. Talwar · 2007
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Privacy integrated queries: an extensible platform for privacy-preserving data analysis
F. D. McSherry · 2009
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Differentially private spatial decompositions
G. Cormode, C. Procopiuc, D. Srivastava, E. Shen, and T. Yu · 2012
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Universally utility-maximizing privacy mechanisms
A. Ghosh, T. Roughgarden, and M. Sundararajan · 2012
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A simple and practical algorithm for differentially private data release
M. Hardt, K. Ligett, and F. McSherry · 2012
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Private convex empirical risk minimization and high-dimensional regression
D. Kifer, A. Smith, and A. Thakurta · 2012
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Private learning and sanitization: Pure vs. approximate differential privacy
A. Beimel, K. Nissim, and U. Stemmer · 2013
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A near-optimal algorithm for differentially-private principal components
K. Chaudhuri, A. D. Sarwate, and K. Sinha · 2013
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On differentially private low rank approximation
M. Kapralov and K. Talwar · 2013
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Differentially private feature selection via stability arguments, and the robustness of the lasso
A. G. Thakurta and A. Smith · 2013
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Private empirical risk minimization: Efficient algorithms and tight error bounds
R. Bassily, A. Smith, and A. Thakurta · 2014
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The large margin mechanism for differentially private maximization
K. Chaudhuri, D. J. Hsu, and S. Song · 2014
Cited alongside, same era.
The algorithmic foundations of differential privacy
C. Dwork, A. Roth, et al · 2014
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Extremal mechanisms for local differential privacy
P. Kairouz, S. Oh, and P. Viswanath · 2014
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Differentially private high-dimensional data publication via sampling-based inference
R. Chen, Q. Xiao, Y. Zhang, and J. Xu · 2015
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Subsampled exponential mechanism: Differential privacy in large output spaces
E. Lantz, K. Boyd, and D. Page · 2015
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Nearly optimal private lasso
K. Talwar, A. G. Thakurta, and L. Zhang · 2015
Cited alongside, same era.
Understanding the sparse vector technique for differential privacy
M. Lyu, D. Su, and N. Li · 2017
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Tight lower bounds for differentially private selection
T. Steinke and J. Ullman · 2017
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Privbayes: Private data release via bayesian networks
J. Zhang, G. Cormode, C. M. Procopiuc, D. Srivastava, and X. Xiao · 2017
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Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising
B. Balle and Y.-X. Wang · 2018
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Stepping-up: The census bureau tries to be a good data steward in the 21stcentury
J. M. Abowd · 2019
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Benefits and pitfalls of the exponential mechanism with applications to hilbert spaces and functional pca
J. Awan and A. Kenney · 2019
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Algorithmic stability for adaptive data analysis
R. Bassily, K. Nissim, A. Smith, T. Steinke, U. Stemmer, and J. Ullman · 2016
Cited alongside, same era.
Principled evaluation of differentially private algorithms using dpbench
M. Hay, A. Machanavajjhala, G. Miklau, Y. Chen, and D. Zhang · 2016
Cited alongside, same era.
Differential privacy without sensitivity
K. Minami, H. Arai, I. Sato, and H. Nakagawa · 2016
Cited alongside, same era.
Lipschitz extensions for node-private graph statistics and the generalized exponential mechanism
S. Raskhodnikova and A. Smith · 2016
Cited alongside, same era.
On the optimality of the exponential mechanism
F. Aldà and H. U. Simon · 2017
Cited alongside, same era.
The price of selection in differential privacy
M. Bafna and J. Ullman · 2017
Cited alongside, same era.
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Implementing the exponential mechanism with base-2 differential privacy
C. Ilvento · 2019
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Private selection from private candidates
J. Liu and K. Talwar · 2019
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Kng: The k-norm gradient mechanism
M. Reimherr and J. Awan · 2019
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Differentially private simple linear regression
D. Alabi, A. McMillan, J. Sarathy, A. Smith, and S. Vadhan · 2020
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Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
H. Asi and J. C. Duchi · 2020
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Optimal differential privacy composition for exponential mechanisms
J. Dong, D. Durfee, and R. Rogers · 2020
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