Multivariate Mutual Information Inspired by Secret-Key Agreement
Autor: | Tie Liu, Tarik Kaced, Ali Al-Bashabsheh, Javad B. Ebrahimi, Chung Chan |
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Rok vydání: | 2015 |
Předmět: |
Theoretical computer science
Conditional mutual information Multivariate mutual information Mutual information Total correlation Electrical and Electronic Engineering Marginal distribution Variation of information Information theory Computer Science::Information Theory Mathematics Interaction information |
Zdroj: | Proceedings of the IEEE. 103:1883-1913 |
ISSN: | 1558-2256 0018-9219 |
Popis: | 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. |
Databáze: | OpenAIRE |
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