2 citations · 3 across the 3 of their papers we have counts for
4 papers
Machine Unlearning for Streaming Forgetting
Shaofei Shen, Chenhao Zhang, Yawen Zhao +3
Machine unlearning aims to remove knowledge of the specific training data in a well-trained model. Currently, machine unlearning methods typically handle all forgetting data in a s…
GENIU: A Restricted Data Access Unlearning for Imbalanced Data
Chenhao Zhang, Shaofei Shen, Yawen Zhao +2
With the increasing emphasis on data privacy, the significance of machine unlearning has grown substantially. Class unlearning, which involves enabling a trained model to forget da…
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
Shaofei Shen, Chenhao Zhang, Yawen Zhao +3
Machine unlearning aims to remove information derived from forgotten data while preserving that of the remaining dataset in a well-trained model. With the increasing emphasis on da…
A Boosting Algorithm for Positive-Unlabeled Learning
Yawen Zhao, Mingzhe Zhang, Chenhao Zhang +3
Positive-unlabeled (PU) learning deals with binary classification problems when only positive (P) and unlabeled (U) data are available. Many recent PU methods are based on neural n…