# Publications

Private Empirical Risk Minimization, Revisited

”, in ICML 2014 Workshop on Learning, Security and Privacy, Beijing, China, 2014. Publisher's VersionAbstract 1405.7085v1.pdfDeclarative Policies for Capability Control

”, in Proceedings of the 27th {IEEE} Computer Security Foundations Symposium, Piscataway, NJ, USA, 2014.Abstract csf14_capflow.pdfSample Complexity Bounds on Differentially Private Learning via Communication Complexity

”, Proceedings of The 27th Conference on Learning Theory (COLT 2014), vol. 35. JMLR Workshop and Conference Proceedings, pp. 1-20, 2014. Publisher's VersionAbstract feldman14b.pdfFaster Private Release of Marginals on Small Databases

”, in Proceedings of the 5th Conference on Innovations in Theoretical Computer Science, New York, NY, USA, 2014, pp. 387–402. Publisher's Version p387-chandrasekaran.pdfFingerprinting Codes and the Price of Approximate Differential Privacy

”, in Proceedings of the 46th Annual ACM Symposium on Theory of Computing, New York, NY, USA, 2014, pp. 1–10. Publisher's Version p1-bun.pdfMechanism Design in Large Games: Incentives and Privacy

”, in Proceedings of the 5th Conference on Innovations in Theoretical Computer Science, New York, NY, USA, 2014, pp. 403–410. Publisher's Version p403-kearns.pdfRedrawing the Boundaries on Purchasing Data from Privacy-sensitive Individuals

”, in Proceedings of the 5th Conference on Innovations in Theoretical Computer Science, New York, NY, USA, 2014, pp. 411–422. Publisher's Version p411-nissim.pdfAn Anti-Folk Theorem for Large Repeated Games with Imperfect Monitoring

”, CoRR, vol. abs/1402.2801, 2014. 1402.2801v1.pdfPrivately Solving Linear Programs

”, in Automata, Languages, and Programming, vol. 8572, Springer Berlin Heidelberg, 2014, pp. 612-624. Publisher's Version 1402.3631v2.pdfEstimation of exchangeable graph models by stochastic blockmodel approximation

”, in Global Conference on Signal and Information Processing (GlobalSIP), 2013 IEEE, 2013, pp. 293-296. chan_costa_airoldi_2013.pdfAnalyzing Graphs with Node Differential Privacy

”, in Proceedings of the 10th Theory of Cryptography Conference on Theory of Cryptography, Berlin, Heidelberg, 2013, pp. 457–476. Publisher's Version chp3a10.10072f978-3-642-36594-2_26.pdfCharacterizing the Sample Complexity of Private Learners

”, in Proceedings of the 4th Conference on Innovations in Theoretical Computer Science, New York, NY, USA, 2013, pp. 97–110. Publisher's Version p97-beimel_1.pdfPrivate Learning and Sanitization: Pure vs. Approximate Differential Privacy

”, in Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, vol. 8096, Springer Berlin Heidelberg, 2013, pp. 363-378. Publisher's Version chp3a10.10072f978-3-642-40328-6_26.pdf- 1 of 3
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