Deep Learning Requires Explicit Regularization for Reliable Predictive Probability

11 Jun 2020Taejong JooUijung Chung

From the statistical learning perspective, complexity control via explicit regularization is a necessity for improving the generalization of over-parameterized models, which deters the memorization of intricate patterns existing only in the training data. However, the impressive generalization performance of over-parameterized neural networks with only implicit regularization challenges this traditional role of explicit regularization... (read more)

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