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RTMS explanation #213

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ludoro opened this issue Jul 11, 2020 · 2 comments
Open

RTMS explanation #213

ludoro opened this issue Jul 11, 2020 · 2 comments
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@ludoro
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ludoro commented Jul 11, 2020

Hello guys! First of all, really cool library.

I have been working on Surrogates.jl, a Julia package that mostly has the same goal.
I am trying to implement from this paper here: "A fast-prediction surrogate model for large datasets" which I believe it's related to this library.
However, I am not understanding how to build the matrix $F$, for each i-esim row I should evaluate the i-esim training point x at some splines, right? The number of columns is the degree of the splines? I am bit confused. Could you shed some light?
@relf
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relf commented Jul 23, 2020

Hi, thanks for the kind word.
You're right the surrogate is related to this paper (link broken in the doc) and well... as far as I am concerned I am not that familiar with this surrogate so I would suggest to refer to the implementation... but maybe you already did?!

@ludoro
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ludoro commented Jul 24, 2020

Yeah, I tried but without much success. I get stuck at page 6 of that paper, when defining the F function. I am not in a hurry so I can maybe wait for someone who is familiar with it :)

@relf relf mentioned this issue Aug 17, 2020
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@relf relf added the question label Sep 8, 2020
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