Privacy-preserving linear programming

Author:

Mangasarian O. L.

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization

Reference11 articles.

1. Chen, K., Liu, L.: Privacy preserving data classification with rotation perturbation. In: Proceedings of the Fifth International Conference of Data Mining (ICDM’05), pp. 589–592. IEEE (2005)

2. Feng X., Zhang Z.: The rank of a random matrix. Appl. Math. Comput. 185, 689–694 (2007)

3. ILOG, Incline Village, Nevada. ILOG CPLEX 9.0 User’s Manual (2003). http://www.ilog.com/products/cplex/

4. Laur, S., Lipmaa, H., Mielikäinen, T.: Cryptographically private support vector machines. In: KDD ’06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 618–624. ACM, New York, NY, USA (2006)

5. Mangasarian, O.L., Wild, E.W.: Privacy-preserving classification of horizontally partitioned data via random kernels. Technical Report 07-03, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, WI, November 2007. In: Stahlbock, R., Crone, S.V., Lessman, S. (eds.) Proceedings of the 2008 International Conference on Data Mining, vol. II, pp. 473–479. DMIN08, Las Vegas (2008)

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