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Bounding Retraining Equivalence and the Deletion Floor in Materials Machine Unlearning
In materials machine learning, closely related retained structures can sustain accurate property predictions even after removing a specific record, rendering post-deletion prediction error an ambiguous metric for machine unlearning. To resolve this ambiguity, we define the deletion floor as the expe
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