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We propose a generic mechanism to efficiently release differentially private synthetic versions of high-dimensional datasets with high utility.
On a method of determining correlation from the ranks of the variates
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A new measure of rank correlation
M. G. Kendall · 1938
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Fonctions de repartition an dimensions et leurs marges
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Transformation of non positive semidefinite correlation matrices
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Computing the nearest correlation matrix-a problem from finance
N. J. Higham · 2002
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Transforming data to satisfy privacy constraints
V. S. Iyengar · 2002
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Complexity of Gröbner basis computation for Semi-regular Overdetermined sequences over F_2 with solutions in F_2
M. Bardet, J.-C. Faugere, and B. Salvy · 2003
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Calibrating noise to sensitivity in private data analysis
C. Dwork, F. McSherry, K. Nissim, and A. Smith · 2006
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An Introduction to Copulas (Springer Series in Statistics)
R. B. Nelsen · 2006
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Robust de-anonymization of large sparse datasets
A. Narayanan and V. Shmatikov · 2008
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On the complexity of differentially private data release: efficient algorithms and hardness results
C. Dwork, M. Naor, O. Reingold, G. N. Rothblum, and S. Vadhan · 2009
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Privacy integrated queries: An extensible platform for privacy-preserving data analysis
F. D. McSherry · 2009
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Broken promises of privacy: Responding to the surprising failure of anonymization
P. Ohm · 2009
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Differential privacy for statistics: What we know and what we want to learn
C. Dwork and A. Smith · 2010
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Boosting and differential privacy
C. Dwork, G. N. Rothblum, and S. Vadhan · 2010
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Optimizing Linear Counting Queries Under Differential Privacy
C. Li, M. Hay, V. Rastogi, G. Miklau, and A. McGregor · 2010
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Interactive privacy via the median mechanism
A. Roth and T. Roughgarden · 2010
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Differential privacy via wavelet transforms
X. Xiao, G. Wang, and J. Gehrke · 2010
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Differential Privacy: A Primer for the Perplexed
C. Dwork, F. McSherry, K. Nissim, and A. Smith · 2011
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A comparative analysis of spearman’s rho and kendall’s tau in normal and contaminated normal models
W. Xu, Y. Hou, Y. Hung, and Y. Zou · 2013
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The Algorithmic Foundations of Differential Privacy
C. Dwork and A. Roth · 2014
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Dual Query: Practical Private Query Release for High Dimensional Data
M. Gaboardi, E. J. G. Arias, J. Hsu, A. Roth, and Z. S. Wu · 2014
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Differentially private synthesization of multi-dimensional data using copula functions
H. Li, L. Xiong, and X. Jiang · 2014
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Privbayes: Private data release via bayesian networks
J. Zhang, G. Cormode, C. M. Procopiuc, D. Srivastava, and X. Xiao · 2014
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Foundations and Methods of Stochastic Simulation: A First Course
B. Nelson · 2015
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Differentially private data release for data mining
N. Mohammed, R. Chen, B. Fung, and P. S. Yu · 2011
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Pcps and the hardness of generating private synthetic data
J. Ullman and S. Vadhan · 2011
Cited alongside, same era.
Differentially private spatial decompositions
G. Cormode, C. Procopiuc, D. Srivastava, E. Shen, and T. Yu · 2012
Cited alongside, same era.
A simple and practical algorithm for differentially private data release
M. Hardt, K. Ligett, and F. McSherry · 2012
Cited alongside, same era.
A learning theory approach to noninteractive database privacy
A. Blum, K. Ligett, and A. Roth · 2013
Cited alongside, same era.
Matrix computations , volume 4
G. H. Golub and C. F. Van Loan · 2013
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Simultaneous private learning of multiple concepts
M. Bun, K. Nissim, and U. Stemmer · 2016
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Mathematical Methods of Statistics (PMS-9) , volume 9
H. Cramér · 2016
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Psi ( { \{ \ \backslash Psi } \} ): a private data sharing interface
M. Gaboardi, J. Honaker, G. King, J. Murtagh, K. Nissim, J. Ullman, and S. Vadhan · 2016
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The Complexity of Differential Privacy
S. Vadhan · 2016
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Differential privacy on finite computers
V. Balcer and S. Vadhan · 2017
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Package ‘copula’, 2017
M. Hofert, I. Kojadinovic, M. Maechler, J. Yan, M. M. Maechler, and M. Suggests · 2017
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Answering n2+O(1) counting queries with differential privacy is hard
J. Ullman · 2029
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