AUC Maximization in the Era of Big Data and AI: A Survey. (arXiv:2203.15046v3 [cs.LG] UPDATED)

Area under the ROC curve, a.k.a. AUC, is a measure of choice for assessing
the performance of a classifier for imbalanced data. AUC maximization refers to
a learning paradigm that learns a predictive model by directly maximizing its
AUC score. It has been studied for more than two decades dating back to late
90s and a huge amount of work has been devoted to AUC maximization since then.
Recently, stochastic AUC maximization for big data and deep AUC maximization
for …

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