Affine Calculus for Constrained Minima of the Kullback–Leibler Divergence
The non-parametric version of Amari’s dually affine Information Geometry provides a practical calculus to perform computations of interest in statistical machine learning. The method uses the notion of a statistical bundle, a mathematical structure that includes both probability densities and random...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2025-03-01
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| Sarja: | Stats |
| Aiheet: | |
| Linkit: | https://www.mdpi.com/2571-905X/8/2/25 |
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