Simple recurrent neural networks for support vector machine training

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.