Fetching the paper…
Reading the bibliography…
Interaction information is one of the multivariate generalizations of mutual information, which expresses the amount information shared among a set of variables, beyond the information, which is shared in any proper subset of those variables.
W. J. McGill, “Multivariate information transmission,” Psychometrika
1954
Earlier work this paper cites.
S. Watanabe, “Information theoretical analysis of multivariate correlation,” IBM Journal of research and development
1960
Earlier work this paper cites.
MIT Press, Cambridge, Massachussets, 1961
R. M. Fano, The Transmission of Information: A Statistical Theory of Communication · 1961
Earlier work this paper cites.
R. W. Yeung, “A new outlook on shannon’s information measures,” IEEE transactions on information theory
1991
Earlier work this paper cites.
T. Tsujishita, “On triple mutual information,” Advances in applied mathematics
1995
Earlier work this paper cites.
M. Studenỳ and J. Vejnarová, “The multiinformation function as a tool for measuring stochastic dependence,” in Learning in graphical models
1998
Earlier work this paper cites.
MIT press, 2000
P. Spirtes, C. N. Glymour, and R. Scheines, Causation, prediction, and search · 2000
Cited alongside, same era.
A. J. Bell, “The co-information lattice,” in Proceedings of the Fifth International Workshop on Independent Component Analysis and Blind Signal Separation: ICA
2003
Cited alongside, same era.
A. Jakulin and I. Bratko, “Quantifying and visualizing attribute interactions,” arXiv preprint cs/0308002
2003
Cited alongside, same era.
Cambridge university press, 2009
J. Pearl, Causality · 2009
Cited alongside, same era.
MIT press, 2009
D. Koller and N. Friedman, Probabilistic graphical models: principles and techniques · 2009
Cited alongside, same era.
C. J. Quinn, N. Kiyavash, and T. P. Coleman, “Equivalence between minimal generative model graphs and directed information graphs,” in Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
C. J. Quinn, N. Kiyavash, and T. P. Coleman, “Efficient methods to compute optimal tree approximations of directed information graphs,” IEEE Transactions on Signal Processing
2013
Later among the works it cites.
D. Janzing, D. Balduzzi, M. Grosse-Wentrup, B. Schölkopf, et al
2013
Later among the works it cites.
2016
Later among the works it cites.
2016
Later among the works it cites.
J. Etesami, N. Kiyavash, and T. Coleman, “Learning minimal latent directed information polytrees,” Neural Computation
2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2011
Cited alongside, same era.
Later among the works it cites.