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Found 2 papers, 2 papers with code
Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning
This leads to the problem of machine unlearning (MU), aiming to eliminate the influence of chosen data points on model performance, while still maintaining the model's utility post-unlearning.
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
To address these challenges, we introduce the concept of 'weight saliency' for MU, drawing parallels with input saliency in model explanation.
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