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Jul 2026

cPU: Consistent Risk Estimator for Positive-Unlabeled Learning.

A novel supervision formulation from a risk perspective is derived: if the class prior is known, the ratio between the positive risk distribution of negative samples and the negative risk distribution of positive samples converges to a fixed value in unlabeled samples.

Yao Zhang, Ke Wang, Jun Tang et al. · 0 citations