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Pré-Publication, Document De Travail Année : 2023

One-step corrected projected stochastic gradient descent for statistical estimation

Youssef Esstafa

Résumé

A generic, fast and asymptotically efficient method for parametric estimation is described. It is based on the projected stochastic gradient descent on the log-likelihood function corrected by a single step of the Fisher scoring algorithm. We show theoretically and by simulations that it is an interesting alternative to the usual stochastic gradient descent with averaging or the adaptative stochastic gradient descent.
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Dates et versions

hal-04122876 , version 1 (08-04-2024)

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  • HAL Id : hal-04122876 , version 1

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Alexandre Brouste, Youssef Esstafa. One-step corrected projected stochastic gradient descent for statistical estimation. 2024. ⟨hal-04122876⟩
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