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