AndrewGrant wrote: ↑
Fri Jan 08, 2021 9:46 am
mvanthoor wrote: ↑
Thu Jan 07, 2021 8:40 pm
fabianVDW wrote: ↑
Thu Jan 07, 2021 4:48 pm
Depending on your mathematical education, you can read https://github.com/AndyGrant/Ethereal/b ... Tuning.pdf
. I recommend atleast some basic knowledge about multivariate calculus. Then it is easy. For more questions on the contents of this, you can also ask Andrew directly I suppose or me here.
I'll try and have a look at it.
I have a passing knowledge of mathematics; what you would learn in high school, and the first 2 years of uni when studying computer science. I know the basics of several maths fields, but I'm not a mathematician. Some of that math hasn't been used for so long that I'll probably have to look it up (think, for example, combinatorial calculations, etc).
The Math is quite light. Simple derivations, with some tricks for absolute value, min, and max, which are likely not taught in school, but are of interesting. Only weird looking thing that is not easy to convince yourself of is the Sigmoid derivation in section 3.something.
For noobs like the problem with your paper is not even math - the problem is that it assumes that developer already understands
how to establish the basic pipeline, how it works, what are the inputs and outputs, etc. Reading about optimizing evaluation tuning
without a clear understanding of it's basics simply doesn't make sense. Obviously your paper is source of brilliancy for experienced
developers. This is one of the main reasons for my own research and emphasizing the basic setup and proof of concept implementation
so that the gap in beginner's understanding is removed.
I've been rereading your PDF many times but the only thing I've realized every next time is that I'm more stupid then I thought)
Lots of questions regarding basics were arising along the way that I wanted to ask...
Only after Ronald Friederich kindly explained be the basic idea of Texel's tuning, calculating mean square error in particular -
only then your work started making sense to me. After Ronald explained me your article regarding the optimizations that going
beyond using gradient decent and how you fought non linearity issues - I've realized how god-level your work is.
The most problem of truly incredible articles in terms of brilliancy and insights is the lack of explanations of basics.
Also the great problem is a focus on tiny little details meanwhile completely dropping the overall pipeline flow.
If you've added the only single paragraph to your article within Texel's tuning method explanation (simply defining the pipeline
and providing pseudo code for the phrase "then he adjusts the weights and recalculates MSE") - more people could make use
of your work, but probably you don't really care about it.
I thought the problem was is my stupidity, but it turned out to be simply in a lack of basic knowledge.
The problem is that there are very very few sources of basic knowledge - maybe only a couple of engines.