A modified SISA architecture with replay and gating achieves effective class removal from trained CNNs on image datasets while preserving accuracy and cutting retraining costs.
Few-shot unlearning by model inversion
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A LoRA-based residual feature alignment method for efficient machine unlearning on pre-trained models by targeting zero residuals on retained data and shifted residuals on unlearned data.
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Machine Unlearning for Class Removal through SISA-based Deep Neural Network Architectures
A modified SISA architecture with replay and gating achieves effective class removal from trained CNNs on image datasets while preserving accuracy and cutting retraining costs.
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Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA
A LoRA-based residual feature alignment method for efficient machine unlearning on pre-trained models by targeting zero residuals on retained data and shifted residuals on unlearned data.