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Abstract:
Most literature on Support Vector Machines (SVMs) concentrate on
the dual optimization problem. In this paper, we would like to point out
that the primal problem can also be solved efficiently, both for linear
and non-linear SVMs, and there is no reason for ignoring it. Moreover, from
the primal point of view, new families of algorithms for large scale SVM
training can be investigated.
