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The convergence of the Stochastic Gradient Descent (SGD) : a self-contained proof

Turinici, Gabriel (2021), The convergence of the Stochastic Gradient Descent (SGD) : a self-contained proof. https://basepub.dauphine.psl.eu/handle/123456789/22154

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convergenceSGD_Turinici2021.pdf (309.9Kb)
Type
Document de travail / Working paper
External document link
https://hal.archives-ouvertes.fr/hal-03184035
Date
2021
Series title
Cahier de recherche du CEREMADE
Published in
Paris
Pages
5
Metadata
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Author(s)
Turinici, Gabriel cc
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Abstract (EN)
We give here a proof of the convergence of the Stochastic Gradient Descent (SGD) in a self-contained manner.
Subjects / Keywords
Stochastic Gradient Descent; Neural Network; SGD; Adam; RMSprop

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    A priori convergence of the Generalized Empirical Interpolation Method 
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