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Optim of Tomorrow #326
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I'd like to add
|
Those are good points. Dispatch based linesearches function value(df, x)
if is_new(x, df.last_x)
df.f_calls += 1
df.f_x = df.f(x)
copy!(df.last_x, x)
end
df.f_x
end Benchmarks |
Yes. A key advantage is that it would remove the need for passing function values into line searches and other things. |
I would like to add:
For the native Julia methods, there's no reason to restrict to |
Congrats!! 🎆 |
aka Optim Roadmap 2.0 aka Make Optim Greater Still...
These lists are up for discussion, I just figured I would start that discussion now. JuliaLang v1.0 is approaching rapidly, with v0.6 feature freeze not far into the future. I am not sure we should tag Optim v1.0 the day JuliaLang starts shipping as non-beta, but it would be cool to have a lot of the current issues sorted out.
Let the number of issues guide you as to what I will tackle first :)
General
df.f(x)
,df.g!(x, stor)
anddf.h!(x, stor)
withvalue(df, x)
,gradient!(df, x)
andhessian!(df, x)
where the oldstorage
argument is embedded indf
switch argument order for gradient and hessian evaluations? #156 optim-julep: define AbstractProblem and make use of it in optimizers #163 Finite differences: shouldn't we count f_calls? #219 Add limits to f_calls, g_calls and h_calls #241 Changes to DifferentiableFunction API #287 OEP: function-objects should keep track of their own call counts #305 OEP: more general state for user-supplied functions #306/
hessian!
interface Can I maximize a function using Optim.jl? #308(I intend to implement this together with the first bullet)through a keyword and a new functionDocumentation
Constrained
Solvers (up for grabs if the person is willing to "maintain")
In general I think we might want to delete feature/solver requests and have a single issue for them, as the requesters are rarely the ones willing to write up and maintain anyways, so the issues always end up idle.
More
... and more! I think 2017 is going to be a good year for Optim.
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