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Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning

We provide a discussion of several recent results which, in certain scenarios, are able to overcome a barrier in distributed stochastic optimization for machine learning. Our focus is the so-called asymptotic network independence property, which is achieved whenever a distributed method executed ove...

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Détails bibliographiques
Publié dans:IEEE Signal Process Mag
Auteurs principaux: Pu, Shi, Olshevsky, Alex, Paschalidis, Ioannis Ch.
Format: Artigo
Langue:Inglês
Publié: 2020
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7977622/
https://ncbi.nlm.nih.gov/pubmed/33746471
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/msp.2020.2975212
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