Regularizing Predictions via Class-wise Self-knowledge Distillation

ICLR 2020 Anonymous

Deep neural networks with millions of parameters may suffer from poor generalizations due to overfitting. To mitigate the issue, we propose a new regularization method that penalizes the predictive distribution between similar samples... (read more)

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