What are the major differences between cost, loss, error, fitness, utility, objective, criterion functions?
How can the sum of squared errors have negative gradient if it's defined as the squared of the error?
Why is the "square error function" sometimes defined with the constant 1/2 and sometimes with the constant 1/m?
Why is the Jensen-Shannon divergence preferred over the KL divergence in measuring the performance of a generative network?
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