Existence, uniqueness, and convergence rates for gradient flows in the training of artificial neural networks with ReLU activation

18 August 2021

Papers citing "Existence, uniqueness, and convergence rates for gradient flows in the training of artificial neural networks with ReLU activation"

5 / 5 papers shown

Title
Normalized gradient flow optimization in the training of ReLU artificial neural networks Simon Eberle Arnulf Jentzen Adrian Riekert G. Weiss 29 0 0 13 Jul 2022
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs Etienne Boursier Loucas Pillaud-Vivien Nicolas Flammarion ODL 21 58 0 02 Jun 2022
Convergence proof for stochastic gradient descent in the training of deep neural networks with ReLU activation for constant target functions Martin Hutzenthaler Arnulf Jentzen Katharina Pohl Adrian Riekert Luca Scarpa MLT 34 6 0 13 Dec 2021
Landscape analysis for shallow neural networks: complete classification of critical points for affine target functions Patrick Cheridito Arnulf Jentzen Florian Rossmannek 24 10 0 19 Mar 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,199 0 16 Aug 2016