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Sifting Common Information from Many Variables
[article]
2017
arXiv
pre-print
Measuring the relationship between any pair of variables is a rich and active area of research that is central to scientific practice. In contrast, characterizing the common information among any group of variables is typically a theoretical exercise with few practical methods for high-dimensional data. A promising solution would be a multivariate generalization of the famous Wyner common information, but this approach relies on solving an apparently intractable optimization problem. We
arXiv:1606.02307v4
fatcat:cdtah57cnfafrky4cbxq5twznq