A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
In this paper we describe a new language for statistical data modelling, which offers a general framework for the representation of elementary and summarydata.Thereare threemain c...
A blind classification algorithm is presented that uses hyperdimensional geometric algorithms to locate a hypothesis, in the form of a convex polytope or hyper-sphere. The convex ...
This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents ...
Networks of sensors and simulation models of the physical environment have been implemented separately, often using agent-based methodologies. Some work has been done in providing...