12 citations · 33 across the 11 of their papers we have counts for
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cs.LG2022★ 1 cited
Minimax AUC Fairness: Efficient Algorithm with Provable Convergence
Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney +1
The use of machine learning models in consequential decision making often exacerbates societal inequity, in particular yielding disparate impact on members of marginalized groups d…
cs.LG2022
AUC Maximization in the Era of Big Data and AI: A Survey
Tianbao Yang, Yiming Ying
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…
cs.LG2022★ 2 cited
Differentially Private SGDA for Minimax Problems
Zhenhuan Yang, Shu Hu, Yunwen Lei +3
Stochastic gradient descent ascent (SGDA) and its variants have been the workhorse for solving minimax problems. However, in contrast to the well-studied stochastic gradient descen…