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[The researchers' approach] is based on stochastic approximation where, in place of a true gradient, a stochastic gradient is chosen using one sample from a known probability distribution.  2, fiche 1, Anglais, - stochastic%20gradient

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Stochastic gradient algorithms are widely used for large-scale learning and inference problems. However, their use in practice is typically guided by heuristics and trial-and-error rather than rigorous, generalizable theory.  5, fiche 2, Anglais, - stochastic%20gradient%20algorithm

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Stochastic gradient descent (SGD) and its variants have established themselves as the go-to algorithms for large-scale machine learning problems with independent samples due to their generalization performance and intrinsic computational advantage.  3, fiche 2, Anglais, - stochastic%20gradient%20algorithm

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