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I eventually used the keep-efficient function from this answer to calculate the Pareto front and used the k-means function to calculate the centroid of the front. This gave me the approximate knee-point of the front, which is usually the optimal solution. One of the calculations was to maximise the distance moved in x direction (dx) vs. minimising the energy ...


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Your understanding seems to be correct (although your explanation isn't completely precise), apart from "adding it to your original gradient vector". You add the gradient vector to the parameters/weights vector. (Note that back-propagation is just the algorithm that computes the gradient vector. The update of the parameters with the gradient of the ...


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