Papers in Stochastic Gradient Optimization Techniques 35
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Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers2021 Information and Inference A Journal of the IMA article Computer Science Stochastic Gradient Optimization Techniques Open access
Bubacarr Bah, Holger Rauhut, Ulrich Terstiege, Michael Westdickenberg
29citations -
Neural network training under semidefinite constraints2022 Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes conference-paper Computer Science Stochastic Gradient Optimization Techniques cited by 1 patent
Patricia Pauli, Niklas Funcke, Dennis Gramlich, Mohamed Amine Msalmi, Frank Allgöwer
10citations -
Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent2020 Lecture notes in computer science conference-paper Computer Science Stochastic Gradient Optimization Techniques
Alper Yegenoglu, Kai Krajsek, Sandra Diaz-Pier, Michaël Herty
7citations -
Smaller generalization error derived for a deep residual neural network compared with shallow networks2022 IMA Journal of Numerical Analysis article Computer Science Stochastic Gradient Optimization Techniques Open access
Aku Kammonen, Jonas Kiessling, Petr Plecháč, Mattias Sandberg, Anders Szepessy, Raul F. Tempone
4citations