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On the convergence of global-optimization fraudulent stochastic algorithms

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  • Miclo, Laurent

Abstract

We introduce and analyse the almost sure convergence of a new stochastic algorithm for the global minimization of Morse functions on compact Riemannian manifolds. This di˙usion process is called fraudulent because it requires the knowledge of minimal value of the function. Its investigation is nevertheless important, since in particular it appears as the limit behavior of non-fraudulent and time-inhomogeneous swarm mean-field algorithms used in global optimization.

Suggested Citation

  • Miclo, Laurent, 2023. "On the convergence of global-optimization fraudulent stochastic algorithms," TSE Working Papers 23-1437, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:128086
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    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2023/wp_tse_1437.pdf
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    References listed on IDEAS

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    1. Jérôme Bolte & Laurent Miclo & Stéphane Villeneuve, 2024. "Swarm gradient dynamics for global optimization: the mean-field limit case," Post-Print hal-04552722, HAL.
    2. Villeneuve, Stéphane & Bolte, Jérôme & Miclo, Laurent, 2022. "Swarm gradient dynamics for global optimization: the mean-field limit case," TSE Working Papers 22-1302, Toulouse School of Economics (TSE).
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    Cited by:

    1. Gadat, Sébastien & De Castro, Yohann & Marteau, Clément, 2023. "FastPart: Over-Parameterized Stochastic Gradient Descent for Sparse optimisation on Measures," TSE Working Papers 23-1494, Toulouse School of Economics (TSE).

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