Meta Dropout: Learning to Perturb Features for Generalization

Hae Beom Lee, Taewook Nam, Eunho Yang +1

A machine learning model that generalizes well should obtain low errors on unseen test examples. Thus, if we know how to optimally perturb training examples to account for test exa…