Invariances in Classification : an efficient SVM implementation
Gaëlle Loosli, Stéphane Canu, S V N Vishwanathan and Alex Smola
In: ASMDA 2005, 17-20 May 2005, Brest, France.
Often, in pattern recognition, complementary knowledge is available.
This could be useful to improve the performance of the recognition system. Part
of this knowledge regards invariances, in particular when treating images or voice
data. Many approaches have been proposed to incorporate invariances in pattern
recognition systems. Some of these approaches require a pre-processing phase, others
integrate the invariances in the algorithms. We present a unifying formulation
of the problem of incorporating invariances into a pattern recognition classiffier and
we extend the SimpleSVM algorithm to handle invariances