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COLING
2002
15 years 6 months ago
A Maximum Entropy-based Word Sense Disambiguation System
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
Armando Suárez, Manuel Palomar
IJON
2000
71views more  IJON 2000»
15 years 6 months ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli
JCNS
2000
67views more  JCNS 2000»
15 years 6 months ago
Renewal-Process Approximation of a Stochastic Threshold Model for Electrical Neural Stimulation
In a recent set of modeling studies we have developed a stochastic threshold model of auditory nerve response to single biphasic electrical pulses (Bruce et al., 1999c) and moderat...
Ian C. Bruce, Laurence S. Irlicht, Mark W. White, ...
IJON
2007
94views more  IJON 2007»
15 years 6 months ago
A method for speeding up feature extraction based on KPCA
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop...
Yong Xu, David Zhang, Fengxi Song, Jing-Yu Yang, Z...
IJPRAI
1998
100views more  IJPRAI 1998»
15 years 6 months ago
Obtaining The Correspondence between Bayesian and Neural Networks
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Athena Stassopoulou, Maria Petrou