Gradient matching empirically recovers implicit regularization effects such as l2 penalties from early stopping and dropout in neural networks.
Dropout: A Simple Way to Prevent Neural Networks from Overfitting.Journal of Machine Learning Research, 15(56):1929–1958
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Estimating Implicit Regularization in Deep Learning
Gradient matching empirically recovers implicit regularization effects such as l2 penalties from early stopping and dropout in neural networks.