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 ...
Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from highreturn/high-risk to low-return/low-risk, and an investor can cho...
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
The problem of clustering is considered, for the case when each data point is a sample generated by a stationary ergodic process. We propose a very natural asymptotic notion of co...
: The rapid progresses in human genome project and biotechnologies result in the sheer volume of datasets associated with in-depth scientific knowledge. Metabolomics is defined as ...