Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning

25 Apr 2019Wei ShenZhenhuan YangYiming YingXiaoming Yuan

In this paper we study the stability and its trade-off with optimization error for stochastic gradient descent (SGD) algorithms in the pairwise learning setting. Pairwise learning refers to a learning task which involves a loss function depending on pairs of instances among which notable examples are bipartite ranking, metric learning, area under ROC (AUC) maximization and minimum error entropy (MEE) principle... (read more)

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