AI RESEARCH
Regularization Implies balancedness in the deep linear network
arXiv CS.LG
•
ArXi:2511.01137v2 Announce Type: replace We use geometric invariant theory (GIT) to study the deep linear network (DLN). The Kempf-Ness theorem is used to establish that the $L^2$ regularizer is minimized on the balanced manifold. We This framework allows us to decompose the