
The emergence of the double descent phenomenon in deep learning can be attributed to over-parameterized models effectively isolating noisy data within the training set, thus diminishing the influence of interpolating these noisy data points.


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unraveling-the-mechanism-of-double-descent-in-deep-learning-the-role-of-noisy-data-and-learned-feature-space


Unraveling the Mechanism of Double Descent in Deep Learning: The Role of Noisy Data and Learned Feature Space
