Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
In this paper we propose a methodology for brain parcellation with anatomical and functional constraints dedicated to fMRI data analysis. The aim is to provide a representation of...
Background: Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of function...
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
We illustrate with two simple examples how Interactive Evolutionary Computation (IEC) can be applied to Exploratory Data Analysis (EDA). IEC is particularly valuable in an EDA cont...