Enabling Training of Neural Networks on Noisy Hardware

Deep neural networks (DNNs) are typically trained using the conventional stochastic gradient descent (SGD) algorithm. However, SGD performs poorly when applied to train networks on non-ideal analog hardware composed of resistive device arrays with non-symmetric conductance modulation characteristics...

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Detalles Bibliográficos
Autor principal: Gokmen, Tayfun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8458875/
https://www.ncbi.nlm.nih.gov/pubmed/34568813
http://dx.doi.org/10.3389/frai.2021.699148

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8458875/
https://www.ncbi.nlm.nih.gov/pubmed/34568813
http://dx.doi.org/10.3389/frai.2021.699148

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