10 citations · 13 across the 3 of their papers we have counts for
4 papers
Non-Convergence and Limit Cycles in the Adam optimizer
Sebastian Bock, Martin Georg Weiß
One of the most popular training algorithms for deep neural networks is the Adaptive Moment Estimation (Adam) introduced by Kingma and Ba. Despite its success in many applications…
Automatic Generation of Grover Quantum Oracles for Arbitrary Data Structures
Raphael Seidel, Colin Kai-Uwe Becker, Sebastian Bock +3
The steadily growing research interest in quantum computing - together with the accompanying technological advances in the realization of quantum hardware - fuels the development o…
Local Convergence of Adaptive Gradient Descent Optimizers
Sebastian Bock, Martin Georg Weiß
Adaptive Moment Estimation (ADAM) is a very popular training algorithm for deep neural networks and belongs to the family of adaptive gradient descent optimizers. However to the be…
An improvement of the convergence proof of the ADAM-Optimizer
Sebastian Bock, Josef Goppold, Martin Weiß
A common way to train neural networks is the Backpropagation. This algorithm includes a gradient descent method, which needs an adaptive step size. In the area of neural networks,…