2026
Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
ICML 2026poster
Real-world data is frequently noisy and ambiguous. In crowdsourcing, for example, human annotators may assign conflicting class labels to the same instances. Partial-label learning (PLL) addresses this challenge by training classifiers when each instance is associated with a set of candidate labels,…