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We have decided to discontinue the publication of preprints on our preprint server as of 1 March 2024. The publication culture within mathematics has changed so much due to the rise of repositories such as ArXiV (www.arxiv.org) that we are encouraging all institute members to make their preprints available there. An institute's repository in its previous form is, therefore, unnecessary. The preprints published to date will remain available here, but we will not add any new preprints here.

MiS Preprint
4/2020

Properties of Unique Information

Johannes Rauh, Maik Schünemann and Jürgen Jost

Abstract

We study the unique information $UI(T:X\setminus Y)$ defined by Bertschinger et al. (2014) within the framework of information decompositions. In particular, we study uniqueness and support of the solutions to the convex optimization problem underlying the definition of $UI$. We identify sufficient conditions for non-uniqueness of solutions with full support in terms of conditional independence constraints and in terms of the cardinalities of $T$, $X$ and $Y$. Our results are based on a reformulation of the first order conditions on the objective function as rank constraints on a matrix of conditional probabilities. These results help to speed up the computation of $UI(T:X\setminus Y)$, most notably when $T$ is binary. Optima in the relative interior of the optimization domain are solutions of linear equations if $T$ is binary. In the all binary case, we obtain a complete picture of where the optimizing probability distributions lie.

Received:
Jan 6, 2020
Published:
Jan 6, 2020
MSC Codes:
94A15, 94A17
Keywords:
information decomposition, Unique Information

Related publications

inJournal
2021 Journal Open Access
Johannes Rauh, Maik Schünemann and Jürgen Jost

Properties of unique information

In: Kybernetika, 57 (2021) 3, pp. 383-403