2025
CaliMatch: Adaptive Calibration for Improving Safe Semi-supervised Learning
ICCV 2025poster
Semi-supervised learning (SSL) uses unlabeled data to improve the performance of machine learning models when labeled data is scarce. However, its real-world applications often face the label distribution mismatch problem, in which the unlabeled dataset includes instances whose ground-truth labels a…