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Lipschitz extensions were recently proposed as a tool for designing node differentially private algorithms.
Über die zusammenziehende und lipschitzsche transformationen
M. Kirszbraun · 1934
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Extension of range of functions
E. J. McShane · 1934
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Embeddings and extensions in analysis , volume 84
J. H. Wells and L. R. Williams · 1975
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Characterizations of almost surely continuous p-stable random fourier series and strongly stationary processes
M. Marcus and G. Pisier · 1984
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Extensions of lipschitz maps into banach spaces
W. B. Johnson, J. Lindenstrauss, and G. Schechtman · 1986
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Extension of lipschitz mappings on metric trees
J. Matoušek · 1990
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Markov chains, riesz transforms and lipschitz maps
K. Ball · 1992
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Geometric nonlinear functional analysis , volume 48
Y. Benyamini and J. Lindenstrauss · 1998
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Random graphs
B. Bollobás · 1998
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Extensions of lipschitz maps into hadamard spaces
U. Lang, B. Pavlović, and V. Schroeder · 2000
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A phase transition phenomenon between the isometric and isomorphic extension problems for holder functions between l
A. Naor · 2001
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Extending lipschitz functions via random metric partitions
J. R. Lee and A. Naor · 2005
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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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Mechanism design via differential privacy
F. McSherry and K. Talwar · 2007
Cited alongside, same era.
Smooth sensitivity and sampling in private data analysis
K. Nissim, S. Raskhodnikova, and A. Smith · 2007
Cited alongside, same era.
Power-Law Distributions in Empirical Data
A. Clauset, C. R. Shalizi, and M. E. J. Newman · 2009
Cited alongside, same era.
Differential privacy and robust statistics
C. Dwork and J. Lei · 2009
Cited alongside, same era.
Accurate estimation of the degree distribution of private networks
M. Hay, C. Li, G. Miklau, and D. Jensen · 2009
Cited alongside, same era.
Differentially private recommender systems: building privacy into the net
F. McSherry and I. Mironov · 2009
Cited alongside, same era.
Differentially private graphical degree sequences and synthetic graphs
V. Karwa and A. B. Slavkovic · 2012
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A differentially private estimator for the stochastic kronecker graph model
D. J. Mir and R. N. Wright · 2012
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Differentially private data analysis of social networks via restricted sensitivity
J. Blocki, A. Blum, A. Datta, and O. Sheffet · 2013
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Recursive mechanism: towards node differential privacy and unrestricted joins
S. Chen and S. Zhou · 2013
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Privacy-preserving data exploration in genome-wide association studies
A. Johnson and V. Shmatikov · 2013
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Analyzing graphs with node-differential privacy
S. P. Kasiviswanathan, K. Nissim, S. Raskhodnikova, and A. Smith · 2013
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Relationship privacy: output perturbation for queries with joins
V. Rastogi, M. Hay, G. Miklau, and D. Suciu · 2009
Cited alongside, same era.
Boosting the Accuracy of Differentially Private Histograms Through Consistency
M. Hay, V. Rastogi, G. Miklau, and D. Suciu · 2010
Cited alongside, same era.
Metric extension operators, vertex sparsifiers and lipschitz extendability
K. Makarychev and Y. Makarychev · 2010
Cited alongside, same era.
Private analysis of graph structure
V. Karwa, S. Raskhodnikova, A. Smith, and G. Yaroslavtsev · 2011
Cited alongside, same era.
The johnson-lindenstrauss transform itself preserves differential privacy
J. Blocki, A. Blum, A. Datta, and O. Sheffet · 2012
Cited alongside, same era.
Iterative constructions and private data release
A. Gupta, A. Roth, and J. Ullman · 2012
Cited alongside, same era.
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Information preservation in statistical privacy and Bayesian estimation of unattributed histograms
B.-R. Lin and D. Kifer · 2013
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The Algorithmic Foundations of Differential Privacy
C. Dwork and A. Roth · 2014
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Inference using noisy degrees: Differentially private β-model and synthetic graphs
V. Karwa and A. Slavkovic · 2014
Later among the works it cites.
Differentially private exponential random graphs
V. Karwa, A. B. Slavkovic, and P. N. Krivitsky · 2014
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Exponential random graph estimation under differential privacy
W. Lu and G. Miklau · 2014
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Differentially private network data release via structural inference
Q. Xiao, R. Chen, and K. Tan · 2014
Later among the works it cites.