-
1
-
-
0002709342
-
Feature selection via concave minimization and support vector machines
-
J. Shavlik, editor, San Francisco, California, Morgan Kaufmann
-
P. S. Bradley and O. L. Mangasarian. Feature selection via concave minimization and support vector machines. In J. Shavlik, editor, Proceedings 15th International Conference on Machine Learning, pages 82-90, San Francisco, California, 1998. Morgan Kaufmann.
-
(1998)
Proceedings 15th International Conference on Machine Learning
, pp. 82-90
-
-
Bradley, P.S.1
Mangasarian, O.L.2
-
6
-
-
34548279044
-
Model selection for support vector machines via uniform design
-
Amsterdam, Elsevier Publishing Company
-
C.-H. Huang, Y.-J. Lee, D.K.J. Lin, and S.-Y. Huang. Model selection for support vector machines via uniform design. In Machine Learning and Robust Data Mining of Computational Statistics and Data Analysis, Amsterdam, 2007. Elsevier Publishing Company.
-
(2007)
Machine Learning and Robust Data Mining of Computational Statistics and Data Analysis
-
-
Huang, C.-H.1
Lee, Y.-J.2
Lin, D.K.J.3
Huang, S.-Y.4
-
7
-
-
11844277921
-
-
ILOG, Incline Village, Nevada. ILOG CPLEX 9.0 User's Manual, 2003. http://www.ilog.com/products/cplex/.
-
(2003)
ILOG CPLEX 9.0 User's Manual
-
-
-
10
-
-
31344447750
-
Random projection-based multiplicative data perturbation for privacy preserving distributed data mining
-
K. Liu, H. Kargupta, and J. Ryan. Random projection-based multiplicative data perturbation for privacy preserving distributed data mining. IEEE Transactions on Knowledge and Data Engineering, 18:92-106, 2006.
-
(2006)
IEEE Transactions on Knowledge and Data Engineering
, vol.18
, pp. 92-106
-
-
Liu, K.1
Kargupta, H.2
Ryan, J.3
-
11
-
-
55149085860
-
Wavelet-based data distortion for privacy-preserving collaborative analysis
-
Technical Report 482-07, Department of Computer Science, University of Kentucky, Lexington, KY 40506
-
L. Liu, J. Wang, Z. Lin, and J. Zhang. Wavelet-based data distortion for privacy-preserving collaborative analysis. Technical Report 482-07, Department of Computer Science, University of Kentucky, Lexington, KY 40506, 2007.
-
(2007)
-
-
Liu, L.1
Wang, J.2
Lin, Z.3
Zhang, J.4
-
12
-
-
0001777975
-
Generalized support vector machines
-
A. Smola, P. Bartlett, B. Scho¨lkopf, and D. Schuurmans, editors, Cambridge, MA, MIT Press
-
O. L. Mangasarian. Generalized support vector machines. In A. Smola, P. Bartlett, B. Scho¨lkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 135-146, Cambridge, MA, 2000. MIT Press.
-
(2000)
Advances in Large Margin Classifiers
, pp. 135-146
-
-
Mangasarian, O.L.1
-
14
-
-
66149147290
-
Privacy-preserving classification of vertically partitioned data via random kernels
-
Technical Report 07-02, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, September
-
O. L. Mangasarian, E. W. Wild, and G. M. Fung. Privacy-preserving classification of vertically partitioned data via random kernels. Technical Report 07-02, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, September 2007.
-
(2007)
-
-
Mangasarian, O.L.1
Wild, E.W.2
Fung, G.M.3
-
15
-
-
0003977889
-
-
MATLAB, The MathWorks, Inc, Natick, MA 01760
-
MATLAB. User's Guide. The MathWorks, Inc., Natick, MA 01760, 1994-2006. http://www.mathworks.com.
-
(1994)
User's Guide
-
-
-
17
-
-
33749576809
-
Cryptographically private support vector machines
-
D. Gunopulos L. Ungar, M. Craven and T. Eliassi-Rad, editors, Philadelphia, August 20-23, ACM, 2006
-
H. Lipmaa S. Laur and T. Mielikäinen. Cryptographically private support vector machines. In D. Gunopulos L. Ungar, M. Craven and T. Eliassi-Rad, editors, Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006, Philadelphia, August 20-23, 2006. ACM, pages 618- 624, 2006.
-
(2006)
Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD
, pp. 618-624
-
-
Lipmaa, H.1
Laur, S.2
Mielikäinen, T.3
-
20
-
-
33745171439
-
Privacy preserving id3 algorithm over horizontally partitioned data
-
IEEE Computer Society
-
M.-J. Xiao, L.-S. Huang, H. Shen, and Y.-L. Luo. Privacy preserving id3 algorithm over horizontally partitioned data. In Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), pages 239-243. IEEE Computer Society, 2005.
-
(2005)
Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05)
, pp. 239-243
-
-
Xiao, M.-J.1
Huang, L.-S.2
Shen, H.3
Luo, Y.-L.4
-
21
-
-
33751023839
-
Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data
-
New York, NY, USA, ACM Press
-
H. Yu, X. Jiang, and J. Vaidya. Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data. In SAC '06: Proceedings of the 2006 ACM symposium on Applied computing, pages 603-610, New York, NY, USA, 2006. ACM Press.
-
(2006)
SAC '06: Proceedings of the 2006 ACM symposium on Applied computing
, pp. 603-610
-
-
Yu, H.1
Jiang, X.2
Vaidya, J.3
-
22
-
-
33745799070
-
Privacy-preserving svm classification on vertically partitioned data
-
Proceedings of PAKDD '06, of, Springer-Verlag, January
-
H. Yu, J. Vaidya, and X. Jiang. Privacy-preserving svm classification on vertically partitioned data. In Proceedings of PAKDD '06, volume 3918 of Lecture Notes in Computer Science, pages 647 - 656. Springer-Verlag, January 2006.
-
(2006)
Lecture Notes in Computer Science
, vol.3918
, pp. 647-656
-
-
Yu, H.1
Vaidya, J.2
Jiang, X.3
|