2020
An Unbiased Risk Estimator for Learning with Augmented Classes
NeurIPS 2020poster
This paper studies the problem of learning with augmented classes (LAC), where augmented classes unobserved in the training data might emerge in the testing phase. Previous studies generally attempt to discover augmented classes by exploiting geometric properties, achieving inspiring empirical perfo…