Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Our work presents a mechanism designed for the selection of the optimal information provider in a multi-agent, heterogeneous and unsupervised monitoring system. The selfadaptation...
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...