
Optimy.io: Optimise mathematical expressions - malmsteen
https://api.optimy.io/
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d--b
I'm sorry but this doesn't make any sense to me. Optimizing mathematical
expressions is not a very useful thing to do, and whenever you need it, you'll
likely have a derivable function, for which gradient based optimization is
much faster.

But most importantly, this can't be applied to arbitrary computer functions
that you can't have a closed formula for.

Also finding a library that does optimization where I can pass a function
pointer is usually easy to find in any language.

Maybe I'm wrong, but as far as I'm concerned, I'll never use that service.

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adenadel
This is a bit nitpicky, but so you're aware: the term is differentiable, not
derivable. You differentiate a function, you don't derive it.

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thanatropism
Essa é uma questão lingüística, não matemática.

Em português há uma diferença diminuta de sentido entre "diferenciável" e
"derivável" (na Análise Matemática mesmo), mas não recordo mais qual.

O inglês sendo o idioma mutante que é, talvez acabe absorvendo essa diferença
de nomenclaturas dessa forma: derivable x differentiable.

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adenadel
I understand that it is simply a difference of language and that the intent is
the same, but in mathematics precision of language is incredibly important.
This is a common error in English.

~~~
fusiongyro
I just want to reflect on the irony of your having no trouble replying to a
comment in Portuguese about how it's important to use the right term. This
whole thing has brightened my day.

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LolWolf
> A (future) extension of this app is the optimisation of functions which
> cannnot be writted as mathematical expressions (such as a PDE model) by
> using user-input values of some points of the function to optimise. If this
> is particularly interesting to you don't hesitate to send a mail.

This is an interesting venue, but how would you go about this without solving
the PDE model, itself? I work in a similar area of manifold learning, where
our objective is a functional of a solution to a PDE (which is, in some sense,
a generalization of that idea), but there seems to be no obvious way of
optimizing this program without solving for at least the eigenfunctions of the
PDE. I'd be curious to hear what the author has in mind.

Additionally, I'm also curious as to what algorithms are being used;
derivative-free (incl. subgradient-free) methods are usually quite sub-optimal
for most classes of problems that I know of, but I'm not sure what the
intended audience is, here, so perhaps this would perform quite well in those
cases?

Anyways, I'd love to test it! But I think HN gave the page the hug-of-death so
it's giving me an error...

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zzz95
Looks good, but it is just another NLP solver in a sea of mature and tested
solver implementations. It will be interesting to get the answers for the
below questions:

\- What is the algorithm being used?

\- How does it compare with other mature optimization engines: e.g. IPOPT,
Knitro SNOPT, NPSOL, etc,...

\- Has the results been published somewhere? Or does there exist a compilation
of results on standard benchmarks?

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ouid
Can you please be more specific about the class of expressions you can
optimize in the title?

It is CLEARLY not any mathematical expression, which means that this is
clickbait.

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wenc
I don't want to pour cold water on someone's hobby project if that is what it
is.

It is quite obvious however that website's description was written by someone
who has not actually studied optimization theory or numerical mathematics (my
fields of study). I worked with large-scale nonlinear nonconvex problems for
over a decade, and there is much more to getting it to work for practical
real-world models than this.

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spaceseaman
Neat!

There seems to be some slight bugs with the input being not read correctly but
this is kind of cool.

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dpcx
Getting errors trying to run the default expression. HN Effect already?

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snissn
Who are your target users?

