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Characterization of Overfitting in Robust Multiclass Classification

Jingyuan Xu · Weiwei Liu

Great Hall & Hall B1+B2 (level 1) #2019
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Wed 13 Dec 3 p.m. PST — 5 p.m. PST


This paper considers the following question: Given the number of classes m, the number of robust accuracy queries k, and the number of test examples in the dataset n, how much can adaptive algorithms robustly overfit the test dataset? We solve this problem by equivalently giving near-matching upper and lower bounds of the robust overfitting bias in multiclass classification problems.

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