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Found 2 papers, 1 papers with code
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
Leveraging this approximation, we adapt the original model to eliminate information from the forgotten data at the representation level.
A Boosting Algorithm for Positive-Unlabeled Learning
This is because AdaPU learns a weak classifier and its weight using a weighted positive-negative (PN) dataset with some negative data weights $-$ the dataset is derived from the original PU data, and the data weights are determined by the current weighted classifier combination, but some data weights are negative.
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