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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Bibliographic Details
Main Authors: Oleksandr Borysenko, Maksym Byshkin
Format: article
Language:EN
Published: Nature Portfolio 2021
Subjects:
R
Q
Online Access:https://doaj.org/article/9ae814904dc54f65a9749af760cb5d73
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