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stat.ML2023★ 1 cited
Approximately Bayes-Optimal Pseudo Label Selection
Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti +2
Semi-supervised learning by self-training heavily relies on pseudo-label selection (PLS). The selection often depends on the initial model fit on labeled data. Early overfitting mi…
stat.ML2022★ 3 cited
Uncertainty-aware Pseudo-label Selection for Positive-Unlabeled Learning
Emilio Dorigatti, Jann Goschenhofer, Benjamin Schubert +2
Positive-unlabeled learning (PUL) aims at learning a binary classifier from only positive and unlabeled training data. Even though real-world applications often involve imbalanced…