Groups
Category
Spectral regularization controls how much a weight matrix can stretch inputs by constraining its largest singular value (spectral norm).
L1 regularization (Lasso) adds a penalty \(\lambda \sum_{i=1}^{p} |w_i|\) to the loss, which pushes many coefficients exactly to zero and performs feature selection.