Optimizing Bivariate Partial Information Decomposition

Abdullah Makkeh; Dirk Oliver Theis

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arXiv · 1802.03947

Optimizing Bivariate Partial Information Decomposition

Abdullah Makkeh·Dirk Oliver Theis

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Abstract

None of the BROJA information decomposition measures $\mbox{SI}, \mbox{CI}, \mbox{UIy}, \mbox{UIz}$ 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.

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Abdullah Makkeh, Dirk Oliver Theis. 2018-02-12. Optimizing Bivariate Partial Information Decomposition. https://arxiv.org/abs/1802.03947

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