MAE-MACD: the Masked Adversarial Contrastive Distillation Algorithm Grounded in Masked Autoencoders
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS（2024）
Key words
Training,Neural networks,Robustness,Contrastive learning,Perturbation methods,Representation learning,Feature extraction,Adversarial samples,adversarial training,contrastive learning,knowledge distillation,masked autoencoder (MAE)
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