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Towards a Unified Theory of Learning and Information
In this paper, we introduce the notion of “learning capacity” for algorithms that learn from data, which is analogous to the Shannon channel capacity for communication systems. We show how “learning capacity” bridges the gap between statistical learning theory and information theory, and we will use...
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| Publicat a: | Entropy (Basel) |
|---|---|
| Autor principal: | |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7516920/ https://ncbi.nlm.nih.gov/pubmed/33286212 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22040438 |
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