• Corpus ID: 244909075

Multi-scale Feature Learning Dynamics: Insights for Double Descent

  title={Multi-scale Feature Learning Dynamics: Insights for Double Descent},
  author={Mohammad Pezeshki and Amartya Mitra and Yoshua Bengio and Guillaume Lajoie},
  booktitle={International Conference on Machine Learning},
An intriguing phenomenon that arises from the high-dimensional learning dynamics of neural networks is the phenomenon of “double descent”. The more commonly studied aspect of this phenomenon corresponds to model-wise double descent where the test error exhibits a second descent with increasing model complexity, beyond the classical U-shaped error curve. In this work, we investigate the origins of the less studied epoch-wise double descent in which the test error undergoes two non-monotonous… 

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