Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This articl...
ABSTRACT. Some works in progress on finite domain constraint solvers concern the implementation of a XML trace of the computation according to the OADymPPaC DTD (for example in GNU...
Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
This paper investigates bootstrapping for statistical parsers to reduce their reliance on manually annotated training data. We consider both a mostly-unsupervised approach, co-tra...
Mark Steedman, Rebecca Hwa, Stephen Clark, Miles O...
We propose a probabilistic model for cellular processes, and an algorithm for discovering them from gene expression data. A process is associated with a set of genes that particip...