Continuity and additivity properties of information decompositions

被引:0
|
作者
Rauh, Johannes [1 ]
Banerjee, Pradeep Kr. [1 ]
Olbrich, Eckehard [1 ]
Montufar, Guido [1 ,2 ]
Jost, Juergen [1 ,3 ,4 ]
机构
[1] Max Planck Inst Math Sci, D-04103 Leipzig, Germany
[2] Univ Calif Los Angeles, Los Angeles, CA 90095 USA
[3] Santa Fe Inst, Santa Fe, NM 87501 USA
[4] ScaDS AI Dresden Leipzig, D-04105 Leipzig, Germany
关键词
Information measures; Mutual information; Bivariate information decomposition; Additivity; Continuity; ENTROPY; BOUNDS;
D O I
10.1016/j.ijar.2023.108979
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Information decompositions quantify how the Shannon information about a given random variable is distributed among several other random variables. Various requirements have been proposed that such a decomposition should satisfy, leading to different candidate solutions. Curiously, however, only two of the original requirements that determined the Shannon information have been considered, namely monotonicity and normalization. Two other important properties, continuity and additivity, have not been considered. In this contribution, we focus on the mutual information of two finite variables Y, Z about a third finite variable S and check which of the decompositions satisfy these two properties. While most of them satisfy continuity, only one of them is both continuous and additive. & COPY; 2023 Elsevier Inc. All rights reserved.
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页数:11
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