Provable Tempered Overfitting of Minimal Nets and Typical Nets
We study the overfitting behavior of fully connected deep Neural Networks (NNs) with binary
weights fitted to perfectly classify a noisy training set. We consider interpolation using both …
weights fitted to perfectly classify a noisy training set. We consider interpolation using both …
The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels
Neural networks are powered by an implicit bias: a tendency of gradient descent to fit
training data in a way that generalizes to unseen data. A recent class of neural network …
training data in a way that generalizes to unseen data. A recent class of neural network …
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes
We study the generalization of two-layer ReLU neural networks in a univariate
nonparametric regression problem with noisy labels. This is a problem where kernels …
nonparametric regression problem with noisy labels. This is a problem where kernels …