Research map / Optimization / Nonconvex and smooth optimization
Stochastic AUC Maximization with Deep Neural Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use AUC maximization with PPD-SG or PPD-AdaGrad instead of cross-entropy SGD | ResNet-20 · Imbalanced Cat&Dog, CIFAR10, CIFAR100, and STL10 tasks | testing AUC | Helped |
| Use PPD-SG or PPD-AdaGrad instead of PGA or OAUC | ResNet-20 · Cat&Dog, CIFAR10, CIFAR100, and STL10 tasks | testing AUC | Helped |
| Use cross-entropy SGD instead of AUC-maximization methods | ResNet-20 · Balanced Cat&Dog and CIFAR10 tasks (ratio equal to 50%) | testing AUC | Helped |
| Use cross-entropy SGD instead of AUC-maximization methods | ResNet-20 · Balanced CIFAR100 and STL10 tasks (ratio equal to 50%) | testing AUC | Hurt |
| Pre-train with SGD, then switch to PPD-SG | ResNet-20 · Cat&Dog, CIFAR10, CIFAR100, and STL10 tasks | testing AUC | Helped |
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