Re:Why train when you can optimize?
by Der_Einzige on Saturday April 30, 2022 @12:49PM
(#31217324)
Is it that neural networks are weak or is it that gradient descent/backprop doesn't do well for finding good local solutions for these kinds of problems?
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My understanding is that it's because extrapolation is difficult in general. Extrapolating the behavior of a periodic function like sine is one thing, but extrapolating the behavior of a 1d function that tends to infinity is another challenge altogether. I happen to be very familiar with the implementation of the inverse CDF of the normal distribution though. My plan is to cook a lot of prior knowledge into the NN. Even if I get it working, the end result will likely seem more like sleight of hand than something truly impressive.