Research map / Optimization / Nonconvex and smooth optimization
Stochastic Proximal Algorithms for AUC Maximization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace smooth Frobenius penalty with elastic net penalty in SPAM | SPAM · SECTOR | testing AUC: 0.8768 to 0.9077 | Helped |
| Use SPAM with Frobenius norm vs. baselines | SPAM-L2 · Table 2 (12 datasets) | testing AUC | No clear effect |
| Stochastic proximal update (SPAM) vs. first-order primal-dual SOLAM | AUC maximization · running time (splice, usps, a9a) | AUC vs CPU time | No clear effect |
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