Multivariate Mutual Information Inspired by Secret-Key Agreement Academic Article

abstract

• 2015 IEEE. The capacity for multiterminal secret-key agreement inspires a natural generalization of Shannon's mutual information from two random variables to multiple random variables. Under a general source model without helpers, the capacity is shown to be equal to the normalized divergence from the joint distribution of the random sources to the product of marginal distributions minimized over partitions of the random sources. The mathematical underpinnings are the works on co-intersecting submodular functions and the principle lattices of partitions of the Dilworth truncation. We clarify the connection to these works and enrich them with information-theoretic interpretations and properties that are useful in solving other related problems in information theory as well as machine learning.

authors

• Liu, Tie

published proceedings

• PROCEEDINGS OF THE IEEE

author list (cited authors)

• Chan, C., Al-Bashabsheh, A., Ebrahimi, J. B., Kaced, T., & Liu, T.

citation count

• 51

complete list of authors

• Chan, Chung||Al-Bashabsheh, Ali||Ebrahimi, Javad B||Kaced, Tarik||Liu, Tie

publication date

• October 2015

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings of the Institute of Electrical and Electronics Engineers (IEEE)  Journal

keywords

• Dilworth Truncation
• Multivariate Mutual Information
• Omnivocality
• Principal Partition
• Principle Lattices Of Partitions
• Secret-key Agreement
• Submodularity

Digital Object Identifier (DOI)

• 10.1109/JPROC.2015.2458316

start page

• 1883

end page

• 1913

volume

• 103

issue

• 10