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Rune Skovbo Johansen

@avi I'm looking into ADAM but all descriptions I could find assume familiarity with stochastic gradient descent. And when I'm looking into that, I can't figure out how to map the terminology to what I'm doing, or if it even applies. In the image here (from Wikipedia) I don't know what the summand Qi functions are supposed to correspond to. I have many parameters/dimensions (104) but I only have one evaluation function. I also don't know if I have anything corresponding to "i-th observation".

Text from Wikipedia: Both statistical estimation and machine learning consider the problem of minimizing an objective function that has the form of a sum: Q ( w ) = 1 n ∑ i = 1 n Q i ( w ) , where the parameter w that minimizes Q ( w ) is to be estimated. Each summand function Q i is typically associated with the i-th observation in the data set (used for training).
Sep 12, 2024, 06:59 AM·Quiet public·Phanpy
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