Accuracy
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems
Neural Information Processing Systems
We then use these approximate subclass labels as a form of noisy supervision in a distributionally robust optimization objective.
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Target alignment in truncated kernel ridge regression
Neural Information Processing Systems
We show that TKRR can achieve a fast rate of convergence in the over-aligned regime.
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Appendix: Boosting Out-of-distribution Detection with Typical Features A Type I error and type II error in OOD detection
Neural Information Processing Systems
In the literature on OOD detection, the type II error is also denoted by "FPR
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