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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/24/11/1611 |