A. Narayanan and V. Shmatikov, How To Break Anonymity of the Netflix Prize Dataset, 2006.

J. A. Calandrino, A. Kilzer, A. Narayanan, E. W. Felten, and V. Shmatikov, "You Might Also Like:" Privacy Risks of Collaborative Filtering, 2011 IEEE Symposium on Security and Privacy, 2011.
DOI : 10.1109/SP.2011.40

C. Dwork, Differential Privacy, ICALP, 2006.
DOI : 10.1007/11787006_1

K. Chaudhuri, C. Monteleoni, and A. D. Sarwate, Differentially Private Empirical Risk Minimization, Journal of Machine Learning Research, 2011.

S. Kasiviswanathan, H. K. Lee, K. Nissim, S. Raskhodnikova, and A. Smith, What Can We Learn Privately, FOCS, 2008.
DOI : 10.1109/focs.2008.27

URL : http://arxiv.org/abs/0803.0924

F. Mcsherry and I. Mironov, Differentially private recommender systems, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, 2009.
DOI : 10.1145/1557019.1557090

A. Smith, Privacy-preserving statistical estimation with optimal convergence rates, Proceedings of the 43rd annual ACM symposium on Theory of computing, STOC '11, 2011.
DOI : 10.1145/1993636.1993743

S. L. Warner, Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias, Journal of the American Statistical Association, vol.60, issue.309, 1965.
DOI : 10.1080/01621459.1965.10480775

A. Mcgregor, I. Mironov, T. Pitassi, O. Reingold, K. Talwar et al., The Limits of Two-Party Differential Privacy, 2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 2010.
DOI : 10.1109/FOCS.2010.14

A. Beimel, S. P. Kasiviswanathan, and K. Nissim, Bounds on the Sample Complexity for Private Learning and Private Data Release, TCC, 2010.

C. Dwork and J. Lei, Differential privacy and robust statistics, Proceedings of the 41st annual ACM symposium on Symposium on theory of computing, STOC '09, 2009.
DOI : 10.1145/1536414.1536466

J. C. Duchi, M. I. Jordan, and M. J. Wainwright, Local privacy and statistical minimax rates, FOCS, 2013.
DOI : 10.1109/focs.2013.53

M. J. Wainwright, Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting, IEEE Transactions on Information Theory, vol.55, issue.12, 2009.
DOI : 10.1109/TIT.2009.2032816

P. W. Holland, K. B. Laskey, and S. Leinhardt, Stochastic blockmodels: First steps, Social Networks, vol.5, issue.2, 1983.
DOI : 10.1016/0378-8733(83)90021-7

D. Tomozei and L. Massoulié, Distributed User Profiling via Spectral Methods, Stochastic Systems, 2014.
DOI : 10.1145/1811039.1811098

URL : https://hal.archives-ouvertes.fr/hal-00976912

N. P. Santhanam and M. J. Wainwright, Information-Theoretic Limits of Selecting Binary Graphical Models in High Dimensions, IEEE Transactions on Information Theory, vol.58, issue.7, p.2639, 2009.
DOI : 10.1109/TIT.2012.2191659

S. Banerjee, N. Hegde, and L. Massoulié, The price of privacy in untrusted recommendation engines, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012.
DOI : 10.1109/Allerton.2012.6483317