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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Autores principales: Oleksandr Borysenko, Maksym Byshkin
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/9ae814904dc54f65a9749af760cb5d73
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