# Tag Info

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I want to make it so that if the correct label is 3, then it will penalize the model less heavily if it classifies a 4 than a 7 because 4 is closer numerically to 3 than 7 is. How do I do this? Really you should not, because the symbols used (Arabic numerals) do not have direct relation to quantity in the same way e.g. tally counts or dots do. They are good ...

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The book Deep Learning by Goodfellow, Bengio, and Courville says (Sec 8.3.3, p 292 in my copy) states that Unfortunately, in the stochastic gradient case, Nesterov momentum does not improve the rate of convergence. I'm not sure why this is, but the theoretical advantage depends on a convex problem, and from this, it sounds like the practical advantage ...

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I agree that this notation is unclear. I would interpret it as follows: Given that the expression is supposed to denote the average norm $|p_i|$ is likely the cardinality of the set $\{p_i\}$. In that case the expression would just be the sum over all norms divided by the number of norms, resulting in the average norm. The authors likely use this ...

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After I've learned a little bit more about the topic, I think I figured out the exact sequence of the algorithm. So, here's my own answer. Please, correct me if I'm wrong. Give an input, forward-propagate it, and generate an output For each output neuron: for each weight connected to the neuron: Given the function C = f(w) (which represents the cost ...

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