Abstract
In this paper, we show the arc length of the optimal ROC curve is an f-divergence. By leveraging this result, we express the arc length using a variational objective and estimate it accurately using positive and negative samples. We show this estimator has a non-parametric convergence rate Op(n−β/4) (β∈(0,1] depends on the smoothness). Using the same technique, we show the surface area sandwiched between the optimal ROC curve and the diagonal can be expressed via a similar variational objective. These new insights lead to a novel two-step classification procedure that maximizes an approximate lower bound of the maximal AUC. Experiments on CIFAR-10 datasets show the proposed two-step procedure achieves good AUC performance in imbalanced binary classification tasks.
| Original language | English |
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| Title of host publication | Advances in Neural Information Processing Systems 35 (NeurIPS 2022) |
| Editors | S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh |
| Publisher | Curran Associates, Inc |
| ISBN (Print) | 9781713871088 |
| Publication status | Published - 9 Dec 2022 |
| Event | NeurIPS 2022: The Thirty-Sixth Annual Conference on Neural Information Processing Systems - New Orleans Convention Center, New Orleans Duration: 28 Nov 2022 → 9 Dec 2022 https://neurips.cc/Conferences/2022 |
Publication series
| Name | Advances in Neural Information Processing Systems |
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| Publisher | Curran Associates, Inc. |
| ISSN (Print) | 1049-5258 |
Conference
| Conference | NeurIPS 2022 |
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| City | New Orleans |
| Period | 28/11/22 → 9/12/22 |
| Internet address |