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In this paper we demonstrate that, ignoring computational constraints, it is possible to privately release synthetic databases that are useful for large classes of queries -- much larger in size than the database itself.
Statistical Learning Theory
V. N. Vapnik · 1998
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Neural Network Learning: Theoretical Foundations
M. Anthony and P. Bartlett · 1999
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An elementary proof of the Johnson-Lindenstrauss Lemma
S. Dasgupta and A. Gupta · 1999
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Learning with Kernels
A. J. Smola and B. Schölkopf · 2002
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Revealing information while preserving privacy
I. Dinur and K. Nissim · 2003
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Privacy-preserving datamining on vertically partitioned databases
C. Dwork and K. Nissim · 2004
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Practical privacy: the SuLQ framework
A. Blum, C. Dwork, F. McSherry, and K. Nissim · 2005
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Kernels as features: On kernels, margins, and low-dimensional mappings
M.F. Balcan, A. Blum, and S. Vempala · 2006
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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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The price of privacy and the limits of LP decoding
C. Dwork, F. McSherry, and K. Talwar · 2007
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Mechanism design via differential privacy
F. McSherry and K. Talwar · 2007
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A learning theory approach to non-interactive database privacy
A. Blum, K. Ligett, and A. Roth · 2008
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New efficient attacks on statistical disclosure control mechanisms
C. Dwork and S. Yekhanin · 2008
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What Can We Learn Privately?
S.P. Kasiviswanathan, H.K. Lee, K. Nissim, S. Raskhodnikova, and A. Smith · 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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Boosting and differential privacy
C. Dwork, G.N. Rothblum, and S. Vadhan · 2010
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Differential Privacy and the Fat Shattering Dimension of Linear Queries
A. Roth · 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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Lower bounds in differential privacy
A. De · 2011
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Privately Releasing Conjunctions and the Statistical Query Barrier
A. Gupta, M. Hardt, A. Roth, and J. Ullman · 2011
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Iterative constructions and private data release
A. Gupta, A. Roth, and J. Ullman · 2011
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A multiplicative weights mechanism for privacy-preserving data analysis
M. Hardt and G.N. Rothblum · 2010
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On the Geometry of Differential Privacy
M. Hardt and K. Talwar · 2010
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The Price of Privately Releasing Contingency Tables and the Spectra of Random Matrices with Correlated Rows
S. Kasiviswanathan, M. Rudelson, A. Smith, and J. Ullman · 2010
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A simple and practical algorithm for differentially private data release
M. Hardt, K. Ligett, and F. McSherry · 2011
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Private data release via learning thresholds
M. Hardt, G.N. Rothblum, and R.A. Servedio · 2011
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PCPs and the hardness of generating private synthetic data
Jonathan Ullman and Salil P. Vadhan · 2011
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