2006/04/11 by Jean‐François Coeurjolly, Coeurjolly, Jean-François, Rémy Drouilhet +3
Computer Science · Physics and Astronomy · #Computability, Logic, AI Algorithms #FOS: Mathematics #Neural Networks and Applications #Statistical Mechanics and Entropy #Statistics Theory (math.ST)
paper · pdf · doi:10.48550/arxiv.math/0604246
openalex publication_date 2006/04/11 · 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.