Classification with Asymmetric Label Noise: Consistency and Maximal Denoising

Gilles Blanchard, Marek Flaska, Gregory Handy +2

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that t…