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Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces
We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research. We show that this model-driven approach may require less training data and can potentially be more generalizable as it shows greater resilience to random attacks...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944352/ https://www.ncbi.nlm.nih.gov/pubmed/33733213 http://dx.doi.org/10.3389/frai.2020.567356 |