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A Differentiation cost function

  1. Nov 17, 2016 #1
    Could someone please help me work through the differentiation in a paper (not homework), im having trouble finding out how they came up with their cost function.

    The loss function is L=wE, where E=(G-Gest)^2 and G=F'F

    The derivative of the loss function wrt F is proportional to F'(G-Gest)

    Can't seem to figure it out.


    Last edited: Nov 17, 2016
  2. jcsd
  3. Nov 17, 2016 #2


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    I have some trouble to understand you:

    Do all functions depend on, say time ##t##, which the primes refer to? And why isn't ##G-G=0##? I first thought it could be the strange notation of a function, but then you defined a single ##G##. And last, could it be ##L \propto F(G-G)'##?
  4. Nov 17, 2016 #3
    Thanks for the response, its the loss function of a neural network, so I've corrected to G and Gest, primes refer to transpose
  5. Nov 17, 2016 #4


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    Perhaps someone else can help, but without a lot more context I have no idea what mathematically we are dealing with here.
  6. Nov 17, 2016 #5
    The specific problem is described on page 4 here https://arxiv.org/pdf/1505.07376v3.pdf
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