CoolMomentum: a method for stochastic optimization by Langevin dynamics with simulated annealing
Abstract 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 a...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
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Nature Portfolio
2021
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| Accès en ligne: | https://doaj.org/article/9ae814904dc54f65a9749af760cb5d73 |
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