[SciPy-Dev] GSoC SciPy Optimization Ideas

[Mazen Sayed]

This sounds really good and more reasonable.

Thanks for your help.



On Sun, Apr 11, 2021 at 7:08 PM Pamphile Roy <roy.pamphile at gmail.com> wrote:

> I tend to agree with Daniel here, randomly choosing 50 points in a
> high-dimensional optimization space is not going to give any advantage. And
> why 50?
>
> The initialization part is one of the most important (and difficult to get
> right) part of any optimization algorithm, but this is mostly true for
> global ones: differential evolution, SHGO, Dual Annealing they’re all have
> their own way. Some of these and many others (especially local algorithms)
> rely on the user to explicitly pass an initial guess and take it from there.
>
>
> Agreed here, the random sampling must not be totally random in order to
> cover the parameter space in the most efficient way.
> The global optimizers all use QMC methods (scipy.stats.qmc) so here you
> can just rely on these too.
>
> Cheers,
> Pamphile
>
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