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Stefan Schoepf

2 accepted papers

2026

Redirection for Erasing Memory (REM): Towards a universal unlearning method for corrupted data

ICLR 2026poster

Machine unlearning is studied for a multitude of tasks, but specialization of unlearning methods to particular tasks has made their systematic comparison challenging. To address this issue, we propose a conceptual space to characterize diverse corrupted data unlearning tasks in vision classifiers. T…

Cited by 0SourceScholar
2024

Fast Machine Unlearning without Retraining through Selective Synaptic Dampening

AAAI 2024technical

Machine unlearning, the ability for a machine learning model to forget, is becoming increasingly important to comply with data privacy regulations, as well as to remove harmful, manipulated, or outdated information. The key challenge lies in forgetting specific information while protecting model per…