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Power-law scaling to assist with key challenges in artificial intelligence
Power-law scaling, a central concept in critical phenomena, is found to be useful in deep learning, where optimized test errors on handwritten digit examples converge as a power-law to zero with database size. For rapid decision making with one training epoch, each example is presented only once to...
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| Pubblicato in: | Sci Rep |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7665018/ https://ncbi.nlm.nih.gov/pubmed/33184422 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-76764-1 |
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