Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove...
In order to provide a concise time-varying SISO channel model, the principle of maximum entropy is applied to scattering function derivation. The resulting model is driven by few p...
A variational level set method is developed for the supervised classification problem. Nonlinear classifier decision boundaries are obtained by minimizing an energy functional tha...
This paper introduces a general framework for defining the entropy of a graph. Our definition is based on a local information graph and on information functionals derived from the...
— Computing the partition function and the marginals of a global probability distribution are two important issues in any probabilistic inference problem. In a previous work, we ...