Not All Samples Are Created Equal: Deep Learning with Importance Sampling

Angelos Katharopoulos, François Fleuret

Deep neural network training spends most of the computation on examples that are properly handled, and could be ignored. We propose to mitigate this phenomenon with a principled im…