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NN
2000
Springer
165views Neural Networks» more  NN 2000»
13 years 9 months ago
Construction of confidence intervals for neural networks based on least squares estimation
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansio...
Isabelle Rivals, Léon Personnaz
EAAI
2006
157views more  EAAI 2006»
13 years 10 months ago
Color reduction and estimation of the number of dominant colors by using a self-growing and self-organized neural gas
A new method for color reduction in a digital image is proposed, which is based on the development of a new neural network classifier and on a new method for Estimation of the Mos...
Antonios Atsalakis, Nikos Papamarkos
NN
1998
Springer
13 years 9 months ago
Statistical estimation of the number of hidden units for feedforward neural networks
The number of required hidden units is statistically estimated for feedforward neural networks that are constructed by adding hidden units one by one. The output error decreases w...
Osamu Fujita
UAI
1997
13 years 11 months ago
Update Rules for Parameter Estimation in Bayesian Networks
This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Eric Bauer, Daphne Koller, Yoram Singer
IJCNN
2008
IEEE
14 years 4 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris