most citedWhen AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee

7 citations · 7 across the 1 of their papers we have counts for

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1 paper

cs.LG2022★ 7 cited

When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee

Dixian Zhu, Gang Li, Bokun Wang +2

In this paper, we propose systematic and efficient gradient-based methods for both one-way and two-way partial AUC (pAUC) maximization that are applicable to deep learning. We prop…