Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers

no code implementations • 12 Oct 2019 • Bubacarr Bah, Holger Rauhut, Ulrich Terstiege, Michael Westdickenberg

We study the convergence of gradient flows related to learning deep linear neural networks (where the activation function is the identity map) from data.