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...
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...
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, ...
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...
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...