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Abstract:
We study the effects of introducing structure in the input
distribution of the data to be learnt by a simple perceptron. We
determine the learning curves within the framework of Statistical
Mechanics. Stepwise generalization occurs as a function of the
number of examples when the distribution of patterns is highly
anisotropic. Although extremely simple, the model seems to capture
the relevant features of a class of Support Vector Machines which
was recently shown to present this behavior.
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