Robust and private Bayesian inference

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8776, Issue , 2014, Pages 291-305

  Dimitrakakis, Christos ^a   Nelson, Blaine ^b   Mitrokotsa, Aikaterini ^a   Rubinstein, Benjamin I P ^c  

^a CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

^b UNIVERSITY OF POTSDAM   (Germany)

^c UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

INFERENCE ENGINES; SAMPLING;

BAYESIAN FRAMEWORKS; BAYESIAN INFERENCE; DIFFERENTIAL PRIVACIES; DISTINGUISHABILITY; FINITE SAMPLES; SAMPLING MECHANISMS;

BAYESIAN NETWORKS;

EID: 84910080986     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-11662-4_21     Document Type: Conference Paper

References (26)

1. Berger, J.O.: Statistical Decision Theory and Bayesian Analysis. Springer (1985)
2. Bickel, P.J., Doksum, K.A.: Mathematical Statistics: Basic Ideas and Selected Topics, vol. 1. Holden-Day Company (2001)
3. Bousquet, O., Elisseeff, A.: Stability and generalization. Journal of Machine Learning Research 2, 499–526 (2002)
4. Chatzikokolakis, K., Andrés, M.E., Bordenabe, N.E., Palamidessi, C.: Broadening the scope of differential privacy using metrics. In: De Cristofaro, E., Wright, M. (eds.) PETS 2013. LNCS, vol. 7981, pp. 82–102. Springer, Heidelberg (2013)
5. Chaudhuri, K., Hsu, D.: Convergence rates for differentially private statistical estimation. In: ICML (2012)
6. Chaudhuri, K., Monteleoni, C., Sarwate, A.D.: Differentially private empirical risk minimization. Journal of Machine Learning Research 12, 1069–1109 (2011)
7. DeGroot, M.H.: Optimal Statistical Decisions. John Wiley & Sons (1970)
8. Dimitrakakis, C., Nelson, B., Mitrokotsa, A., Rubinstein, B.: Robust and private Bayesian inference. Technical report, arXiv:1306.1066 (2014)
9. Duchi, J.C., Jordan, M.I., Wainwright, M.J.: Local privacy and statistical minimax rates. Technical report, arXiv:1302.3203 (2013)
10. Dwork, C.: Differential privacy. In: Bugliesi, M., Preneel, B., Sassone, V.,Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4052, pp. 1–12. Springer, Heidelberg (2006)
11. Dwork, C., Lei, J.: Differential privacy and robust statistics. In: STOC, pp. 371–380 (2009)
12. Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: Halevi, S., Rabin, T. (eds.) TCC 2006. LNCS, vol. 3876, pp. 265–284. Springer, Heidelberg (2006)
13. Dwork, C., Smith, A.: Differential privacy for statistics: What we know and what we want to learn. Journal of Privacy and Confidentiality 1(2), 135–154 (2009)
14. Fedotov, A.A., Harremöes, P., Topsoe, F.: Refinements of Pinsker’s inequality. IEEE Transactions on Information Theory 49(6), 1491–1498 (2003)
15. Grünwald, P.D., Dawid, A.P.: Game theory, maximum entropy, minimum discrepancy, and robust bayesian decision theory. The Annals of Statistics 32(4), 1367–1433 (2004)
16. Hall, R., Rinaldo, A., Wasserman, L.: Differential privacy for functions and functional data. Journal of Machine Learning Research 14, 703–727 (2013)
17. Hampel, F.R., Ronchetti, E.M., Rousseeuw, P.J., Stahel, W.A.: Robust Statistics: The Approach Based on Influence Functions. John Wiley and Sons (1986)
18. Huber, P.J.: Robust Statistics. John Wiley and Sons (1981)
19. McSherry, F., Talwar, K.: Mechanism design via differential privacy. In: FOCS, pp. 94–103 (2007)
20. Mir, D.: Differentially-private learning and information theory. In: Proceedings of the 2012 Joint EDBT/ICDT Workshops, pp. 206–210. ACM (2012)
21. Norkin, V.: Stochastic Lipschitz functions. Cybernetics and Systems Analysis 22(2), 226–233 (1986)
22. Rubinstein, B.I.P., Bartlett, P.L., Huang, L., Taft, N.: Learning in a large function space: Privacy-preserving mechanisms for SVM learning. Journal of Privacy and Confidentiality 4(1) (2012)
23. Wasserman, L., Zhou, S.: A statistical framework for differential privacy. Journal of the American Statistical Association 105(489), 375–389 (2010)
24. Weissman, T., Ordentlich, E., Seroussi, G., Verdu, S., Weinberger, M.J.: Inequalities for the L1 deviation of the empirical distribution. Technical report, Hewlett- Packard Labs (2003)
25. Williams, O., McSherry, F.: Probabilistic inference and differential privacy. In: NIPS, pp. 2451–2459 (2010)
26. Xiao, Y., Xiong, L.: Bayesian inference under differential privacy. Technical report, arXiv:1203.0617 (2012)