Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes

1 code implementation • NeurIPS 2021 • Sara Sangalli, Ertunc Erdil, Andreas Hoetker, Olivio Donati, Ender Konukoglu

Such class imbalance is ubiquitous in clinical applications and very crucial to handle because the classes with fewer samples most often correspond to critical cases (e. g., cancer) where misclassifications can have severe consequences.

Binary Classification Multi-class Classification