A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
Since tacit knowledge such as know-how and experiences is hard to be managed effectively using information technology, it is recently proposed that providing an appropriate expert...
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the nu...