Back prop agat ion C an G ive Rise to Spurious Local
نویسنده
چکیده
We give an example of a neural net withou t hidden layers and with a sigmoid transfer funct ion, together with a training set of binary vectors, for which the sum of the squared errors, regarded as a function of the weights, has a local minimum which is not a global minimum. The example consists of a set of 125 t raining instances, with four weights and a th reshold to be learned. We do not know if substantially smaller binary examples exist.
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