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math.OC2026
Convergence of gradient flow for learning convolutional neural networks
Jona-Maria Diederen, Holger Rauhut, Ulrich Terstiege
Convolutional neural networks are widely used in imaging and image recognition. Learning such networks from training data leads to the minimization of a non-convex function. This m…
math.OC2019
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers
Bubacarr Bah, Holger Rauhut, Ulrich Terstiege +1
We study the convergence of gradient flows related to learning deep linear neural networks (where the activation function is the identity map) from data. In this case, the composit…