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 di...

Dinoflagellates in the genus Symbiodinium are best known as endosymbionts of corals and other invertebrate as well as protist hosts, but also exist free-living in coastal environments. Despite their importance in marine ecosystems, less than 10 loci have been used to explore phylogenetic relationships in this group, and only the multi-copy nuclear ribosomal Internal Transcribed Spacer (ITS) reg...

To compare with experiment it is vital that theoretical predictions are finite. Beyond leading order in perturbation theory many processes contain infrared divergences. It is often argued that these singularities are eliminated at the level of the inclusive cross-section [1,2]. During this talk I will show that the infrared divergences are still poorly understood. I also expose some questionabl...

Clustering algorithms start with a fixed divergence, which captures the possibly asymmetric distance between a sample and a centroid. In the mixture model setting, the sample distribution plays the same role. When all attributes have the same topology and dispersion, the data are said to be homogeneous. If the prior knowledge of the distribution is inaccurate or the set of plausible distributio...