-
1
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
Pittsburgh, Pennsylvania, United States
-
Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992). A training algorithm for optimal margin classifiers. Proceedings of the Fifth Annual Workshop on Computational Learning Theory (pp. 144-152). Pittsburgh, Pennsylvania, United States.
-
(1992)
Proceedings of the Fifth Annual Workshop on Computational Learning Theory
, pp. 144-152
-
-
Boser, B.E.1
Guyon, I.M.2
Vapnik, V.N.3
-
3
-
-
27144489164
-
A tutorial on support vector machines for pattern recognition
-
Burges, C. J. C. (1998). A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2, 121-167.
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, pp. 121-167
-
-
Burges, C.J.C.1
-
4
-
-
84898957872
-
Improving the accuracy and speed of support vector learning machines
-
M. Mozer, M. Jordan and T. Petsche (Eds.). Cambridge, MA: MIT Press
-
Burges, C. J. C., & Schoelkopf, B. (1997). Improving the accuracy and speed of support vector learning machines. In M. Mozer, M. Jordan and T. Petsche (Eds.), Advances in neural information processing systems 9, 375-381. Cambridge, MA: MIT Press.
-
(1997)
Advances in Neural Information Processing Systems
, vol.9
, pp. 375-381
-
-
Burges, C.J.C.1
Schoelkopf, B.2
-
5
-
-
34249753618
-
Support-vector networks
-
Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20, 273-297.
-
(1995)
Machine Learning
, vol.20
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
8
-
-
84957069814
-
Text categorization with support vector machines: Learning with many relevant features
-
Berlin: Springer
-
Joachims, T. (1998). Text categorization with support vector machines: Learning with many relevant features. Proceedings of the European Conference on Machine Learning (pp. 137-142). Berlin: Springer.
-
(1998)
Proceedings of the European Conference on Machine Learning
, pp. 137-142
-
-
Joachims, T.1
-
9
-
-
1942484901
-
The pre-image problem in kernel methods
-
Washington, B.C., USA
-
Kwok, J., & Tsang, I. (2003). The pre-image problem in kernel methods. In Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003) (pp. 408-415). Washington, B.C., USA.
-
(2003)
Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003)
, pp. 408-415
-
-
Kwok, J.1
Tsang, I.2
-
10
-
-
0002859310
-
Learning algorithms for classification: A comparison on handwritten digit recognition
-
LeCun, Y., Botou, L., Jackel, L., Drucker, H., Cortes, C., Denker, J., Guyon, I., Muller, U., Sackinger, E., Simard, P., & Vapnik, V. (1995). Learning algorithms for classification: A comparison on handwritten digit recognition. Neural Networks, 261-276.
-
(1995)
Neural Networks
, pp. 261-276
-
-
Lecun, Y.1
Botou, L.2
Jackel, L.3
Drucker, H.4
Cortes, C.5
Denker, J.6
Guyon, I.7
Muller, U.8
Sackinger, E.9
Simard, P.10
Vapnik, V.11
-
11
-
-
0043166439
-
Handwritten digit recognition: Benchmarking of state-of-the-art techniques
-
Liu, C., Nakashima, K., Sako, H., & Fujisawa, H. (2003). Handwritten digit recognition: benchmarking of state-of-the-art techniques. Pattern Recognition, 36, 2271-2285.
-
(2003)
Pattern Recognition
, vol.36
, pp. 2271-2285
-
-
Liu, C.1
Nakashima, K.2
Sako, H.3
Fujisawa, H.4
-
12
-
-
84898970836
-
Kernel pea and de-noising in feature spaces
-
M. S. Kearns, S. A. Solla and D. A. Cohn (Eds.). Cambridge, MA: MIT Press
-
Mika, S., Schoelkopf, B., Smola, A., Muller, K.-R., Scholz, M., & Ratsch, G. (1999). Kernel pea and de-noising in feature spaces. In M. S. Kearns, S. A. Solla and D. A. Cohn (Eds.), Advances in neural information procesmng systems 11, 536-542. Cambridge, MA: MIT Press.
-
(1999)
Advances in Neural Information Procesmng Systems
, vol.11
, pp. 536-542
-
-
Mika, S.1
Schoelkopf, B.2
Smola, A.3
Muller, K.-R.4
Scholz, M.5
Ratsch, G.6
-
14
-
-
0004161838
-
-
Cambridge University Press
-
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (2002). Numerical recipes in c++ : the art of scientific computing. Cambridge University Press.
-
(2002)
Numerical Recipes in C++ : The Art of Scientific Computing
-
-
Press, W.H.1
Teukolsky, S.A.2
Vetterling, W.T.3
Flannery, B.P.4
-
15
-
-
0032594954
-
Input space versus feature space in kernel-based methods
-
Schoelkopf, B., Mika, S., Burges, C. J. C., Knirsch, P., Muller, K., Ratsch, G., & Smola, A. J. (1999). Input space versus feature space in kernel-based methods. IEEE Trans. Neural Networks, 10, 1000-1017.
-
(1999)
IEEE Trans. Neural Networks
, vol.10
, pp. 1000-1017
-
-
Schoelkopf, B.1
Mika, S.2
Burges, C.J.C.3
Knirsch, P.4
Muller, K.5
Ratsch, G.6
Smola, A.J.7
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