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1
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0026966646
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A training algorithm for optimal margin classifiers
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D. Haussler, editor, Pittsburgh, PA, ACM Press
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E. Boser, I .M. Guyon, and V. N. Vapnik. A training algorithm for optimal margin classifiers. In D. Haussler, editor, Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory, pages 144-152, Pittsburgh, PA, 1992. ACM Press.
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(1992)
Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory
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Boser, E.1
Guyon, I.M.2
Vapnik, V.N.3
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2
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85089251671
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Comparison of classifier methods: A case study in handwritten digit recognition
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Jerusalem, IEEE Computer Society Press
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L. Bottou, C. Cortes, J. S. Denker, H. Drucker, I. Guyon, L. D. Jackel, Y. LeCun, U. A. Müller, E. Sackinger, P. Simard, and V. Vapnik. Comparison of classifier methods: A case study in handwritten digit recognition. In Proceedings of the 12th International Conference on Pattern Recognition and Neural Networks, Jerusalem, pages 77 - 87. IEEE Computer Society Press, 1994.
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(1994)
Proceedings of the 12th International Conference on Pattern Recognition and Neural Networks
, pp. 77-87
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Bottou, L.1
Cortes, C.2
Denker, J.S.3
Drucker, H.4
Guyon, I.5
Jackel, L.D.6
LeCun, Y.7
Müller, U.A.8
Sackinger, E.9
Simard, P.10
Vapnik, V.11
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3
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34249753618
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Support vector networks
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C. Cortes and V. Vapnik. Support vector networks. Machine Learning, 20:273 - 297, 1995.
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(1995)
Machine Learning
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Cortes, C.1
Vapnik, V.2
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4
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0003893955
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R. Oldenbourg Verlag, Munich, ISBN 3-486-24632-1
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B. Scholkopf. Support Vector Learning. R. Oldenbourg Verlag, Munich, 1997. ISBN 3-486-24632-1.
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(1997)
Support Vector Learning
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Scholkopf, B.1
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5
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84902142380
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Incorporating invariances in support vector learning machines
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C. vonderMalsburg, W. von Seelen, J. C. Vorbriiggen, and B. Sendhoff, editors, Berlin, Springer Lecture Notes in Computer Science
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B. Scholkopf, C. Burges, and V. Vapnik. Incorporating invariances in support vector learning machines. In C. vonderMalsburg, W. von Seelen, J. C. Vorbriiggen, and B. Sendhoff, editors, Artificial Neural Networks-ICANN'96, pages 47 - 52, Berlin, 1996a. Springer Lecture Notes in Computer Science, Vol. 1112.
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(1996)
Artificial Neural Networks-ICANN'96
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Scholkopf, B.1
Burges, C.2
Vapnik, V.3
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7
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0003137923
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Efficient pattern recognition using a new transformation distance
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S. J. Hanson, J. D. Cowan, and C. L. Giles, editors, San Mateo, CA, Morgan Kaufmann
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P. Simard, Y. LeCun, and J. Denker. Efficient pattern recognition using a new transformation distance. In S. J. Hanson, J. D. Cowan, and C. L. Giles, editors, Advances in Neural Information Processing Systems 5, pages 50-58, San Mateo, CA, 1993. Morgan Kaufmann.
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Advances in Neural Information Processing Systems
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Simard, P.1
LeCun, Y.2
Denker, J.3
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8
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0001440803
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Tangent prop - formalism for specifying selected invariances in an adaptive network
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J. E. Moody, S. J. Hanson, and R. P. Lippmann, editors, San Mateo, CA, Morgan Kaufmann
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P. Simard, B. Victorri, Y. LeCun, and J. Denker. Tangent prop - formalism for specifying selected invariances in an adaptive network. In J. E. Moody, S. J. Hanson, and R. P. Lippmann, editors, Advances in Neural Information Processing Systems 4, pages 895- 903, San Mateo, CA, 1992. Morgan Kaufmann.
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Advances in Neural Information Processing Systems
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Simard, P.1
Victorri, B.2
Lecun, Y.3
Denker, J.4
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10
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0004272441
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[in Russian]. Nauka, Moscow, (German Translation: W. Wapnik & A. Tscherwonenkis, Theorie der Zeichenerkennungy Akademie-Verlag, Berlin, 1979)
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V. Vapnik and A. Chervonenkis. Theory of Pattern Recognition [in Russian]. Nauka, Moscow, 1974. (German Translation: W. Wapnik & A. Tscherwonenkis, Theorie der Zeichenerkennungy Akademie-Verlag, Berlin, 1979).
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(1974)
Theory of Pattern Recognition
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Vapnik, V.1
Chervonenkis, A.2
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