2006/04/11 by Jean-François Coeurjolly, Jean‐François Coeurjolly, Coeurjolly, Jean-François +4
Computer Science · Mathematics · Physics and Astronomy · #Computability, Logic, AI Algorithms #FOS: Mathematics #Neural Networks and Applications #Statistical Mechanics and Entropy #Statistics Theory (math.ST) #math.ST #stat.TH
paper · pdf · doi:10.48550/arxiv.math/0604246
36 pages
openalex publication_date 2006/04/11 · arxiv created 2006/11/13 · arxiv updated 2016/08/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.