Four sample biased datasets as input to AFLite (top). Blue and orange indicate two different classes. Only the original two dimensions are shown, not the bias features. For the dataset on the left, with the highest separation, we flip some labels at random, so even an RBF kernel cannot achieve perfect performance. AFLite makes the data more challenging for the models (bottom).

Cite our paper:

@inproceedings{Bras2020AdversarialFO,