Normalized information-based divergences
  This paper is devoted to the mathematical study of some divergences based on the mutual information well-suited to categorical random vectors. These divergences are generalizations of the "entropy distance" and "information distance". Their main characteristic is that they combine a complexity term and the mutual information. We then introduce the notion of (normalized) information-based divergence, propose several examples and discuss their mathematical properties in particular in some prediction framework. 
Jean-Fran\c{c}ois Coeurjolly (LABSAD), R\'emy Drouilhet (LABSAD),   Jean-Fran\c{c}ois Robineau (LABSAD)