-
1
-
-
0032631788
-
Function approximations by coupling neural networks and genetic programming trees with oblique decision trees
-
Yeun, Y. S.; Lee, K. H.; Yang Y. S. Function approximations by coupling neural networks and genetic programming trees with oblique decision trees. Artificial Intelligence Eng. 1999, 13(3), 223-239.
-
(1999)
Artificial Intelligence Eng.
, vol.13
, Issue.3
, pp. 223-239
-
-
Yeun, Y.S.1
Lee, K.H.2
Yang, Y.S.3
-
2
-
-
0034767488
-
A spiking neural network architecture for nonlinear function approximation
-
Iannella, N.; Back, A. D. A spiking neural network architecture for nonlinear function approximation. Neural Networks 2001, 14(6-7), 933-939.
-
(2001)
Neural Networks
, vol.14
, Issue.6-7
, pp. 933-939
-
-
Iannella, N.1
Back, A.D.2
-
3
-
-
0002678008
-
Quantitative structure property relationship for the estimation of boiling point and flash point using a radial basis function neural network
-
Tetteh, J.; Suzuki, T.; Metcalfe, E.; Howells, S. Quantitative Structure Property Relationship for the Estimation of Boiling Point and Flash Point Using a Radial Basis Function Neural Network. J. Chem. Inf. Comput. Sci. 1999, 39, 491-507.
-
(1999)
J. Chem. Inf. Comput. Sci.
, vol.39
, pp. 491-507
-
-
Tetteh, J.1
Suzuki, T.2
Metcalfe, E.3
Howells, S.4
-
4
-
-
0036589069
-
Quantitative prediction of liquid chromatography retention of n-benzylideneanilines based on quantum chemical parameters and radial basis function neural network
-
Xiang, Y. H.; Liu, M. C., Zhang, X. Y.; Zhang, R. S.; Hu, Z. D.; Fan, B. T. Quantitative Prediction of Liquid Chromatography Retention of N-Benzylideneanilines Based on Quantum Chemical Parameters and Radial Basis Function Neural Network. J. Chem. Inf. Comput. Sci. 2002, 42, 592-597.
-
(2002)
J. Chem. Inf. Comput. Sci.
, vol.42
, pp. 592-597
-
-
Xiang, Y.H.1
Liu, M.C.2
Zhang, X.Y.3
Zhang, R.S.4
Hu, Z.D.5
Fan, B.T.6
-
6
-
-
0002859310
-
Learning algorithms for classification: A comparison on handwritten digit recognition, neural networks: The statistical mechanics perspective
-
Oh, J. H., Kwon, C., Cho, S., Eds.
-
Can, Y.; Jackle, L. D.; Botton, L. et al. Learning Algorithms for Classification: A Comparison on Handwritten Digit Recognition, Neural Networks: The Statistical Mechanics Perspective; Oh, J. H., Kwon, C., Cho, S., Eds.; World Scientific: 1995; pp 261-276.
-
(1995)
World Scientific
, pp. 261-276
-
-
Can, Y.1
Jackle, L.D.2
Botton, L.3
-
7
-
-
84902205493
-
Comparison of view-based object recognition algorithms using realistic 3D models
-
Artificial Neural Networks - ICANN'96; Malsburg, C. V. D., Seelen, W. V., Vorbrüggen, J. C., Sendhoff, B., Eds.
-
Blanz, V.; Schölkopf, B.; Bülthoff, H.; Surges, C.; Vapnik, V.; Vetter, T. Comparison of view-based object recognition algorithms using realistic 3D models. In Artificial Neural Networks - ICANN'96; Malsburg, C. V. D., Seelen, W. V., Vorbrüggen, J. C., Sendhoff, B., Eds.; Springer Lecture Notes in Computer Science, Berlin, 1996; Vol. 1112, pp 251-256.
-
(1996)
Springer Lecture Notes in Computer Science, Berlin
, vol.1112
, pp. 251-256
-
-
Blanz, V.1
Schölkopf, B.2
Bülthoff, H.3
Surges, C.4
Vapnik, V.5
Vetter, T.6
-
9
-
-
0003425660
-
Text categorization with support vector machines
-
University of Dortmund
-
Joachims, T. Text Categorization with Support Vector Machines. LS - Techical Report, No. 23; University of Dortmund: 1997. ftp:// ftpal.informatik.unidortmunddc/pub/report23.ps.Z.
-
(1997)
LS - Techical Report, No. 23
, vol.23
-
-
Joachims, T.1
-
10
-
-
0034740222
-
Drug design by machine learning: Support vector machines for pharmaceutical data analysis
-
Burbidge, R.; Trotter, M.; Buxton, B.; Holden, S.; Drug design by machine learning: support vector machines for pharmaceutical data analysis. Comput. Chem. 2001, 26, 5-14
-
(2001)
Comput. Chem.
, vol.26
, pp. 5-14
-
-
Burbidge, R.1
Trotter, M.2
Buxton, B.3
Holden, S.4
-
11
-
-
0036007085
-
Prediction of protein structural classes by support vector machines
-
Cai, Y. D.; Liu, X. J.; Xu, X. B.; Chou, K. C. Prediction of protein structural classes by support vector machines. Comput. Chem. 2002, 26, 293-296.
-
(2002)
Comput. Chem.
, vol.26
, pp. 293-296
-
-
Cai, Y.D.1
Liu, X.J.2
Xu, X.B.3
Chou, K.C.4
-
12
-
-
0037134796
-
Identifying genes related to drug anticancer mechanisms using support vector machine
-
Bao, L.; Sun, Z. R. Identifying genes related to drug anticancer mechanisms using support vector machine. FEBS Lett. 2002, 521, 109-114.
-
(2002)
FEBS Lett.
, vol.521
, pp. 109-114
-
-
Bao, L.1
Sun, Z.R.2
-
14
-
-
0001260194
-
Extract simplification of support vector solutions
-
Tom D.; Kevin, E. G.; Annette, M.; Extract Simplification of Support Vector Solutions. J. Machine Learning Res. 2001, 2, 293-297.
-
(2001)
J. Machine Learning Res.
, vol.2
, pp. 293-297
-
-
Tom, D.1
Kevin, E.G.2
Annette, M.3
-
15
-
-
27144489164
-
A tutorial on support vector machines for pattern recognition
-
Burges, C. J. C. A tutorial on support vector machines for pattern recognition. Data Mining Knowledge Discovery 1998, 2(2), 1-47.
-
(1998)
Data Mining Knowledge Discovery
, vol.2
, Issue.2
, pp. 1-47
-
-
Burges, C.J.C.1
-
16
-
-
0345688978
-
Determination of the spread parameter in the Gaussian kernel for classification and regression
-
In press
-
Wang, W. J.; Xu, Z. B.; Lu, W. Z., Zhang, X. Y. Determination of the spread parameter in the Gaussian kernel for classification and regression. Neurocomputing In press.
-
Neurocomputing
-
-
Wang, W.J.1
Xu, Z.B.2
Lu, W.Z.3
Zhang, X.Y.4
-
18
-
-
77955821238
-
Support vector machines experts for time series forecasting
-
in press
-
Cao, L. J. Support vector machines experts for time series forecasting. Neurocomputing 2002, in press.
-
(2002)
Neurocomputing
-
-
Cao, L.J.1
|