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Communication Dans Un Congrès Année : 2022

A gradient descent algorithm built on approximate discrete gradients

Résumé

We propose an optimization method obtained by the approximation of a novel discretization approach for gradient dynamics recently proposed by the authors. It is shown that the proposed algorithm ensures convergence for all amplitudes of the step size, contrarily to classical implementations.
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Dates et versions

hal-04227956 , version 1 (04-10-2023)

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Alessio Moreschini, Mattia Mattioni, Salvatore Monaco, Dorothée Normand-Cyrot. A gradient descent algorithm built on approximate discrete gradients. 26th International Conference on System Theory, Control and Computing (ICSTCC 2022), Oct 2022, Sinaia, Romania. pp.343-348, ⟨10.1109/ICSTCC55426.2022.9931872⟩. ⟨hal-04227956⟩
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