2 papers
stat.ML2026
Self-Regularized Learning Methods
Max Schölpple, Liu Fanghui, Ingo Steinwart
We introduce a general framework for analyzing learning algorithms based on the notion of self-regularization, which captures implicit complexity control without requiring explicit…
stat.ML2025
Beyond ReLU: How Activations Affect Neural Kernels and Random Wide Networks
David Holzmüller, Max Schölpple
In recent years, the neural tangent kernel (NTK) and neural network Gaussian process kernel (NNGP) have given theoreticians tractable limiting cases of fully connected neural netwo…