English

Optimizing Bivariate Partial Information Decomposition

Optimization and Control 2018-02-13 v1

Abstract

None of the BROJA information decomposition measures \mboxSI,\mboxCI,\mboxUIy,\mboxUIz\mbox{SI}, \mbox{CI}, \mbox{UIy}, \mbox{UIz} are convex or concave over the probability simplex. In this paper, we provide formulas for the sub-gradient and super-gradients of any of the information decomposition measures. Then we apply these results to obtain an optimum of some of these information decomposition measures when optimized over a constrained set of probability distributions.

Cite

@article{arxiv.1802.03947,
  title  = {Optimizing Bivariate Partial Information Decomposition},
  author = {Abdullah Makkeh and Dirk Oliver Theis},
  journal= {arXiv preprint arXiv:1802.03947},
  year   = {2018}
}
R2 v1 2026-06-23T00:18:56.718Z