Abstract: In this talk, I will present our recent research efforts of developing a deep learning library called LibAUC, which is applicable for solving a variety of compositional measures. I will first present some background about optimization for machine learning and then introduce you a broad family of compositional measures/objectives called X-measure. Then I will focus on optimizing two measures, namely areas under ROC curves (AUROC) and areas under Precision-Recall curves (AUPRC) by talking about our theoretical research for designing algorithms and improving complexities, and our applied research for winning medical AI challenges.

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