This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
In this paper we present an original framework to extract representative groups from a dataset, and we validate it over a novel case study. The framework specifies the application ...
In this paper we present a method for clustering SAGE (Serial Analysis of Gene Expression) data to detect similarities and dissimilarities between different types of cancer on the...
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...