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cs.LG2024
Label Smoothing Improves Machine Unlearning
Zonglin Di, Zhaowei Zhu, Jinghan Jia +6
The objective of machine unlearning (MU) is to eliminate previously learned data from a model. However, it is challenging to strike a balance between computation cost and performan…
cs.LG2024★ 1 cited
Adversarial Machine Unlearning
Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik +1
This paper focuses on the challenge of machine unlearning, aiming to remove the influence of specific training data on machine learning models. Traditionally, the development of un…