Communication Efficient Algorithms for Bounding and Approximating the Empirical Entropy in Distributed Systems

The empirical entropy is a key statistical measure of data frequency vectors, enabling one to estimate how diverse the data are. From the computational point of view, it is important to quickly compute, approximate, or bound the entropy. In a distributed system, the representative (“global”) frequen...

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Detalles Bibliográficos
Autores principales: Shahar, Amit, Alfassi, Yuval, Keren, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689552/
https://www.ncbi.nlm.nih.gov/pubmed/36359705
http://dx.doi.org/10.3390/e24111611

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689552/
https://www.ncbi.nlm.nih.gov/pubmed/36359705
http://dx.doi.org/10.3390/e24111611

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