Using class-center vectors to build support vector machines
Xuegong Zhang
Page(s): 3-11
Digital Object Identifier 10.1109/NNSP.1999.788117 Abstract
| Full Text: PDF (356 KB)
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Margin-like quantities and generalized approximate cross validation
for support vector machines
Wahba, G.; Yi Lin; Hao Zhang
Page(s): 12-20
Digital Object Identifier 10.1109/NNSP.1999.788118 Abstract
| Full Text: PDF (304 KB)
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SUPANOVA: a sparse, transparent modelling approach
Gunn, S.R.; Brown, M.
Page(s): 21-30
Digital Object Identifier 10.1109/NNSP.1999.788119 Abstract
| Full Text: PDF (456 KB)
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Sequential support vector machines
de Freitas, N.; Milo, M.; Clarkson, P.; Niranjan, M.; Gee, A.
Page(s): 31-40
Digital Object Identifier 10.1109/NNSP.1999.788120 Abstract
| Full Text: PDF (420 KB)
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Fisher discriminant analysis with kernels
Mika, S.; Ratsch, G.; Weston, J.; Scholkopf, B.; Mullers, K.R.
Page(s): 41-48
Digital Object Identifier 10.1109/NNSP.1999.788121 Abstract
| Full Text: PDF (464 KB)
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The application of support vector machines with Gaussian kernels
for overcoming co-channel interference
Albu, F.; Martinez, D.
Page(s): 49-57
Digital Object Identifier 10.1109/NNSP.1999.788122 Abstract
| Full Text: PDF (356 KB)
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A Gaussianity measure for blind source separation insensitive to
the sign of kurtosis
Hsiao-Chun Wu; Principe, J.C.
Page(s): 58-66
Digital Object Identifier 10.1109/NNSP.1999.788123 Abstract
| Full Text: PDF (332 KB)
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Robust machine fault detection with independent component analysis
and support vector data description
Ypma, A.; Tax, D.M.J.; Duin, R.P.W.
Page(s): 67-76
Digital Object Identifier 10.1109/NNSP.1999.788124 Abstract
| Full Text: PDF (428 KB)
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View-based 3D object recognition with support vector machines
Roobaert, D.; Van Hulle, M.M.
Page(s): 77-84
Digital Object Identifier 10.1109/NNSP.1999.788125 Abstract
| Full Text: PDF (412 KB)
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Gradient based adaptive regularization
Eigenmann, R.; Nossek, J.A.
Page(s): 87-94
Digital Object Identifier 10.1109/NNSP.1999.788126 Abstract
| Full Text: PDF (288 KB)
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Global stability in delayed cellular neural networks
Weight estimation for the learning of modular perceptron networks
Lee, T.P.; Shin-Chin Fu
Page(s): 103-111
Digital Object Identifier 10.1109/NNSP.1999.788128 Abstract
| Full Text: PDF (344 KB)
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General statistical inference by an approximate application of the
maximum entropy principle
Lian Yan; Miller, D.J.
Page(s): 112-121
Digital Object Identifier 10.1109/NNSP.1999.788129 Abstract
| Full Text: PDF (492 KB)
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On training piecewise linear networks
Atiya, A.; Gad, E.; Shaheen, S.; El-Dessouky, A.
Page(s): 122-131
Digital Object Identifier 10.1109/NNSP.1999.788130 Abstract
| Full Text: PDF (380 KB)
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A control theory formulation for random variate generation
Magdon-Ismail, M.; Atiya, A.F.
Page(s): 132-138
Digital Object Identifier 10.1109/NNSP.1999.788131 Abstract
| Full Text: PDF (264 KB)
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A spiking neural network architecture for nonlinear function
approximation
Iannella, N.; Back, A.
Page(s): 139-146
Digital Object Identifier 10.1109/NNSP.1999.788132 Abstract
| Full Text: PDF (268 KB)
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Partial likelihood methods for probability density estimation
Ni, H.; Adali, T.; Bo Wang
Page(s): 147-156
Digital Object Identifier 10.1109/NNSP.1999.788133 Abstract
| Full Text: PDF (428 KB)
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Why a nonlinear solution for a linear problem? [channel
equalization]
Approximation by random networks with bounded number of layers
Gelenbe, E.; Zhi-Wong Mao; Yan-Da Li
Page(s): 166-175
Digital Object Identifier 10.1109/NNSP.1999.788135 Abstract
| Full Text: PDF (396 KB)
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Natural power method for fast subspace tracking
Yingbo Hua; Yong Xiang; Tiangping Chen; Abed-Meraim, K.; Yongfeng Miao
Page(s): 176-185
Digital Object Identifier 10.1109/NNSP.1999.788136 Abstract
| Full Text: PDF (352 KB)
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Robust neural network online learning in time-variant regression
models
Briegel, T.; Tresp, V.
Page(s): 186-194
Digital Object Identifier 10.1109/NNSP.1999.788137 Abstract
| Full Text: PDF (384 KB)
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Hidden Markov mixtures of experts for prediction of non-stationary
dynamics
Liehr, S.; Pawelzik, K.; Kohlmorgen, J.; Lemm, S.; Muller, K.R.
Page(s): 195-204
Digital Object Identifier 10.1109/NNSP.1999.788138 Abstract
| Full Text: PDF (468 KB)
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A comparison among feature selection methods based on trained
networks
Redondo, M.F.; Espinosa, C.H.
Page(s): 205-214
Digital Object Identifier 10.1109/NNSP.1999.788139 Abstract
| Full Text: PDF (480 KB)
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Sizing of the multilayer perceptron via modular networks
Chandrasekaran, H.; Kim, K.K.; Manry, M.T.
Page(s): 215-224
Digital Object Identifier 10.1109/NNSP.1999.788140 Abstract
| Full Text: PDF (404 KB)
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