Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Simple recurrent neural networks for support vector machine training

: Sifa, R.; Paurat, D.; Trabold, D.; Bauckhage, C.


Kůrková, V.:
Artificial Neural Networks and Machine Learning - ICANN 2018. Proceedings, Part III : 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018
Cham: Springer International Publishing, 2018 (Lecture Notes in Computer Science 11141)
ISBN: 978-3-030-01424-7
ISBN: 978-3-030-01423-0
ISBN: 978-3-030-01425-4
International Conference on Artificial Neural Networks (ICANN) <27, 2018, Rhodes>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
01/S18038C; ML2R
Conference Paper
Fraunhofer IAIS ()

We show how to implement a simple procedure for support vector machine training as a recurrent neural network. Invoking the fact that support vector machines can be trained using Frank-Wolfe optimization which in turn can be seen as a form of reservoir computing, we obtain a model that is of simpler structure and can be implemented more easily than those proposed in previous contributions.