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CoolMomentum: a method for stochastic optimization by Langevin dynamics with simulated annealing
Deep learning applications require global optimization of non-convex objective functions, which have multiple local minima. The same problem is often found in physical simulations and may be resolved by the methods of Langevin dynamics with Simulated Annealing, which is a well-established approach f...
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| Pubblicato in: | Sci Rep |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8139967/ https://ncbi.nlm.nih.gov/pubmed/34021212 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-021-90144-3 |
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