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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
S.13-22
International Conference on Artificial Neural Networks (ICANN) <27, 2018, Rhodes>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
01/S18038C; ML2R
Englisch
Konferenzbeitrag
Fraunhofer IAIS ()

Abstract
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.

: http://publica.fraunhofer.de/dokumente/N-516067.html