  We study the typical properties of polynomial Support Vector Machines within
a Statistical Mechanics approach that allows us to analyze the effect of
different normalizations of the features. If the normalization is adecuately
chosen, there is a hierarchical learning of features of increasing order as a
function of the training set size.

Disordered Systems and Neural Networks