Towards an information-theory for hierarchical partitions

Perotti, Juan I., Almeira, Nahuel, Saracco, Fabio

arXiv.org Machine Learning 

Complex systems often require descriptions covering a wide range of scales and organization levels, where a hierarchical decomposition of their description into components and sub-components is often convenient. To better understand the hierarchical decomposition of complex systems, in this work we prove a few essential results that contribute to the development of an information-theory for hierarchical-partitions.

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