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Beyond Moments: Extending the Maximum Entropy Principle to Feature Distribution Constraints
The maximum entropy principle introduced by Jaynes proposes that a data distribution should maximize the entropy subject to constraints imposed by the available knowledge. Jaynes provided a solution for the case when constraints were imposed on the expected value of a set of scalar functions of the...
Autor principal: | Baggenstoss, Paul M. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513173/ https://www.ncbi.nlm.nih.gov/pubmed/33265739 http://dx.doi.org/10.3390/e20090650 |
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