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Found 2 papers, 2 papers with code
Fair Machine Unlearning: Data Removal while Mitigating Disparities
In this work, we demonstrate that most efficient unlearning methods cannot accommodate popular fairness interventions, and we propose the first fair machine unlearning method that can efficiently unlearn data instances from a fair objective.
Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
Quantifying the perceptual alignment of model gradients via their similarity with the gradients of generative models, we show that off-manifold robustness correlates well with perceptual alignment.
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