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.
The partial information decomposition of generative neural network models
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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.