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Volumn 19, Issue , 2011, Pages 155-186

Sample complexity bounds for differentially private learning

Author keywords

List of keywords

Indexed keywords

LEARNING ALGORITHMS;

EID: 84885588035     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (132)

References (38)
  • 1
    • 0041783510 scopus 로고    scopus 로고
    • Privacy-preserving data mining
    • ISSN 0163-5808. doi: http://doi.acm.org/10.1145/335191.335438
    • R. Agrawal and R. Srikant. Privacy-preserving data mining. SIGMOD Rec., 29(2):439-450, 2000. ISSN 0163-5808. doi: http://doi.acm.org/10.1145/335191. 335438.
    • (2000) SIGMOD Rec. , vol.29 , Issue.2 , pp. 439-450
    • Agrawal, R.1    Srikant, R.2
  • 3
    • 0141693771 scopus 로고    scopus 로고
    • An elementary introduction to modern convex geometry
    • Silvio Levy, editor
    • K. Ball. An elementary introduction to modern convex geometry. In Silvio Levy, editor, Flavors of Geometry, volume 31. 1997.
    • (1997) Flavors of Geometry , vol.31
    • Ball, K.1
  • 4
    • 35448955720 scopus 로고    scopus 로고
    • Privacy, accuracy, and consistency too: A holistic solution to contingency table release
    • B. Barak, K. Chaudhuri, C. Dwork, S. Kale, F. McSherry, and K. Talwar. Privacy, accuracy, and consistency too: a holistic solution to contingency table release. In PODS, pages 273-282, 2007.
    • (2007) PODS , pp. 273-282
    • Barak, B.1    Chaudhuri, K.2    Dwork, C.3    Kale, S.4    McSherry, F.5    Talwar, K.6
  • 5
    • 77949617188 scopus 로고    scopus 로고
    • Bounds on the sample complexity for private learning and private data release
    • Amos Beimel, Shiva Prasad Kasiviswanathan, and Kobbi Nissim. Bounds on the sample complexity for private learning and private data release. In TCC, pages 437-454, 2010.
    • (2010) TCC , pp. 437-454
    • Beimel, A.1    Kasiviswanathan, S.P.2    Nissim, K.3
  • 6
    • 33244468835 scopus 로고    scopus 로고
    • Practical privacy: The sulq framework
    • A. Blum, C. Dwork, F. McSherry, and K. Nissim. Practical privacy: the sulq framework. In PODS, pages 128-138, 2005.
    • (2005) PODS , pp. 128-138
    • Blum, A.1    Dwork, C.2    McSherry, F.3    Nissim, K.4
  • 7
    • 57049136138 scopus 로고    scopus 로고
    • A learning theory approach to non-interactive database privacy
    • R. E. Ladner and C. Dwork, editors, ACM, ISBN 978-1-60558-047-0
    • A. Blum, K. Ligett, and A. Roth. A learning theory approach to non-interactive database privacy. In R. E. Ladner and C. Dwork, editors, STOC, pages 609-618. ACM, 2008. ISBN 978-1-60558-047-0.
    • (2008) STOC , pp. 609-618
    • Blum, A.1    Ligett, K.2    Roth, A.3
  • 8
    • 67349151635 scopus 로고    scopus 로고
    • Using the doubling dimension to analyze the generalization of learning algorithms
    • Nader H. Bshouty, Yi Li, and Philip M. Long. Using the doubling dimension to analyze the generalization of learning algorithms. J. Comput. Syst. Sci., 75(6):323-335, 2009.
    • (2009) J. Comput. Syst. Sci. , vol.75 , Issue.6 , pp. 323-335
    • Bshouty, N.H.1    Li, Y.2    Long, P.M.3
  • 11
    • 33749566820 scopus 로고    scopus 로고
    • When random sampling preserves privacy
    • Cynthia Dwork, editor, CRYPTO, Springer, ISBN 3-540-37432-9
    • Kamalika Chaudhuri and Nina Mishra. When random sampling preserves privacy. In Cynthia Dwork, editor, CRYPTO, volume 4117 of Lecture Notes in Computer Science, pages 198-213. Springer, 2006. ISBN 3-540-37432-9.
    • (2006) Lecture Notes in Computer Science , vol.4117 , pp. 198-213
    • Chaudhuri, K.1    Mishra, N.2
  • 12
    • 71049162986 scopus 로고    scopus 로고
    • Coarse sample complexity bounds for active learning
    • Sanjoy Dasgupta. Coarse sample complexity bounds for active learning. In NIPS, 2005.
    • (2005) NIPS
    • Dasgupta, S.1
  • 14
    • 1142263341 scopus 로고    scopus 로고
    • Limiting privacy breaches in privacy preserving data mining
    • A. Evfimievski, J. Gehrke, and R. Srikant. Limiting privacy breaches in privacy preserving data mining. In PODS, pages 211-222, 2003.
    • (2003) PODS , pp. 211-222
    • Evfimievski, A.1    Gehrke, J.2    Srikant, R.3
  • 15
    • 0031209604 scopus 로고    scopus 로고
    • Selective sampling using the query by committee algorithm
    • Yoav Freund, H. Sebastian Seung, Eli Shamir, and Naftali Tishby. Selective sampling using the query by committee algorithm. Machine Learning, 28(2-3): 133-168, 1997.
    • (1997) Machine Learning , vol.28 , Issue.2-3 , pp. 133-168
    • Freund, Y.1    Seung, H.S.2    Shamir, E.3    Tishby, N.4
  • 16
    • 65449162734 scopus 로고    scopus 로고
    • Composition attacks and auxiliary information in data privacy
    • Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanathan, and Adam Smith. Composition attacks and auxiliary information in data privacy. In KDD, pages 265-273, 2008a.
    • (2008) KDD , pp. 265-273
    • Srivatsava, R.G.1    Kasiviswanathan, S.P.2    Smith, A.3
  • 17
    • 65449162734 scopus 로고    scopus 로고
    • Composition attacks and auxiliary information in data privacy
    • Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanathan, and Adam Smith. Composition attacks and auxiliary information in data privacy. In KDD, pages 265-273, 2008b.
    • (2008) KDD , pp. 265-273
    • Srivatsava, R.G.1    Kasiviswanathan, S.P.2    Smith, A.3
  • 18
    • 0344550482 scopus 로고    scopus 로고
    • Bounded geometries, fractals, and low-distortion embeddings
    • Anupam Gupta, Robert Krauthgamer, and James R. Lee. Bounded geometries, fractals, and low-distortion embeddings. In FOCS, pages 534-543, 2003.
    • (2003) FOCS , pp. 534-543
    • Gupta, A.1    Krauthgamer, R.2    Lee, J.R.3
  • 19
    • 79959740503 scopus 로고    scopus 로고
    • Privately releasing conjunctions and the statistical query barrier
    • Anupam Gupta, Moritz Hardt, Aaron Roth, and Jonathan Ullman. Privately releasing conjunctions and the statistical query barrier. In STOC, 2011.
    • (2011) STOC
    • Gupta, A.1    Hardt, M.2    Roth, A.3    Ullman, J.4
  • 20
    • 77954711905 scopus 로고    scopus 로고
    • On the geometry of differential privacy
    • Moritz Hardt and Kunal Talwar. On the geometry of differential privacy. In STOC, pages 705-714, 2010.
    • (2010) STOC , pp. 705-714
    • Hardt, M.1    Talwar, K.2
  • 23
    • 57949117235 scopus 로고    scopus 로고
    • A note on differential privacy: Defining resistance to arbitrary side information
    • abs/0803.3946
    • Shiva Prasad Kasiviswanathan and Adam Smith. A note on differential privacy: Defining resistance to arbitrary side information. CoRR, abs/0803.3946, 2008.
    • (2008) CoRR
    • Kasiviswanathan, S.P.1    Smith, A.2
  • 25
    • 0029403808 scopus 로고
    • On the sample complexity of pac learning halfspaces against the uniform distribution
    • P. M. Long. On the sample complexity of pac learning halfspaces against the uniform distribution. IEEE Transactions on Neural Networks, 6(6):1556559, 1995.
    • (1995) IEEE Transactions on Neural Networks , vol.6 , Issue.6 , pp. 1556559
    • Long, P.M.1
  • 27
    • 0031637037 scopus 로고    scopus 로고
    • Some pac-bayesian theorems
    • David A. McAllester. Some pac-bayesian theorems. In COLT, pages 230-234, 1998.
    • (1998) COLT , pp. 230-234
    • McAllester, D.A.1
  • 28
    • 70350678967 scopus 로고    scopus 로고
    • Differentially private recommender systems: Building privacy into the net
    • New York, NY, USA, ACM. ISBN 978-1-60558-495-9. doi: http://doi.acm.org/ 10.1145/1557019.1557090
    • Frank McSherry and Ilya Mironov. Differentially private recommender systems: building privacy into the net. In KDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 627-636, New York, NY, USA, 2009. ACM. ISBN 978-1-60558-495-9. doi: http://doi.acm.org/10.1145/1557019.1557090.
    • (2009) KDD '09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pp. 627-636
    • McSherry, F.1    Mironov, I.2
  • 29
    • 46749128577 scopus 로고    scopus 로고
    • Mechanism design via differential privacy
    • Frank McSherry and Kunal Talwar. Mechanism design via differential privacy. In FOCS, pages 94-103, 2007.
    • (2007) FOCS , pp. 94-103
    • McSherry, F.1    Talwar, K.2
  • 30
    • 50249142450 scopus 로고    scopus 로고
    • Robust de-anonymization of large sparse datasets
    • Oakland, CA, USA., May IEEE Computer Society
    • Arvind Narayanan and Vitaly Shmatikov. Robust de-anonymization of large sparse datasets. In IEEE Symposium on Security and Privacy, pages 111-125, Oakland, CA, USA., May 2008. IEEE Computer Society.
    • (2008) IEEE Symposium on Security and Privacy , pp. 111-125
    • Narayanan, A.1    Shmatikov, V.2
  • 31
    • 35448955271 scopus 로고    scopus 로고
    • Smooth sensitivity and sampling in private data analysis
    • In David S. Johnson and Uriel Feige, editors, ACM, ISBN 978-1-59593-631-8
    • Kobbi Nissim, Sofya Raskhodnikova, and Adam Smith. Smooth sensitivity and sampling in private data analysis. In David S. Johnson and Uriel Feige, editors, STOC, pages 75-84. ACM, 2007. ISBN 978-1-59593-631-8.
    • (2007) STOC , pp. 75-84
    • Nissim, K.1    Raskhodnikova, S.2    Smith, A.3
  • 33
    • 78149311849 scopus 로고    scopus 로고
    • Differential privacy and the fat-shattering dimension of linear queries
    • Aaron Roth. Differential privacy and the fat-shattering dimension of linear queries. In APPROX-RANDOM, pages 683-695, 2010.
    • (2010) APPROX-RANDOM , pp. 683-695
    • Roth, A.1
  • 35
    • 0001024505 scopus 로고
    • On the uniform convergence of relative frequencies of events to their probabilities
    • V. N. Vapnik and A. Y. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and Its Applications, 16(2):264-280, 1971.
    • (1971) Theory of Probability and Its Applications , vol.16 , Issue.2 , pp. 264-280
    • Vapnik, V.N.1    Chervonenkis, A.Y.2
  • 36
    • 74049130896 scopus 로고    scopus 로고
    • Learning your identity and disease from research papers: Information leaks in genome wide association study
    • Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang, and Xiao yong Zhou. Learning your identity and disease from research papers: information leaks in genome wide association study. In ACM Conference on Computer and Communications Security, pages 534-544, 2009.
    • (2009) ACM Conference on Computer and Communications Security , pp. 534-544
    • Wang, R.1    Li, Y.F.2    Wang, X.3    Tang, H.4    Zhou, X.Y.5
  • 37
    • 0020312165 scopus 로고
    • Protocols for secure computations (extended abstract)
    • Andrew Chi-Chih Yao. Protocols for secure computations (extended abstract). In FOCS, pages 160-164, 1982.
    • (1982) FOCS , pp. 160-164
    • Yao, A.C.-C.1


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