2022
AdaFocal: Calibration-aware Adaptive Focal Loss
NeurIPS 2022accept
Much recent work has been devoted to the problem of ensuring that a neural network's confidence scores match the true probability of being correct, i.e. the calibration problem. Of note, it was found that training with focal loss leads to better calibration than cross-entropy while achieving similar…