Minimization with respect to divergences and applications - Sorbonne Université Access content directly
Book Sections Year : 2021

Minimization with respect to divergences and applications


We apply divergences to project a prior guess discrete probability law on pq elements towards a subspace defined by fixed margins constraints µ and ν on p and q elements respectively. We justify why the Kullback-Leibler and the Chi-square divergences are two canonical choices based on a 1991 work of Imre Csiszár. Besides we interpret the so called indetermination resulting from the second divergence as a construction to reduce couple matchings. Eventually, we demonstrate how both resulting probabilities arise in two information theory applications: guessing problem and task partitioning where some optimization remains to minimize a divergence projection.
Fichier principal
Vignette du fichier
Bertrand et al. - 2021 - Minimization with Respect to Divergences and Appli.pdf (307.72 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03329875 , version 1 (31-08-2021)



Pierre Bertrand, Michel Broniatowski, Jean-François Marcotorchino. Minimization with respect to divergences and applications. GSI 2021: Geometric Science of Information, pp.818-828, 2021, ⟨10.1007/978-3-030-80209-7_88⟩. ⟨hal-03329875⟩
35 View
27 Download



Gmail Facebook Twitter LinkedIn More