Groups
Category
Spectral regularization controls how much a weight matrix can stretch inputs by constraining its largest singular value (spectral norm).
Double descent describes how test error first follows the classic U-shape with increasing model complexity, spikes near the interpolation threshold, and then drops again in the highly overparameterized regime.