A Multi-kernel Framework for Inductive Semi-supervised Learning
Xilan Tian, Gilles Gasso and Stéphane Canu
In: ESANN 2011, 27 - 29 April 2011, Bruges, Belgium.
We investigate the benet of combining both cluster assump-
tion and manifold assumption underlying most of the semi-supervised al-
gorithms using the
exibility and the eciency of multi-kernel learning.
The multiple kernel version of Transductive SVM (a cluster assumption
based approach) is proposed and it is solved based on DC (Dierence of
Convex functions) programming. Promising results on benchmark data
sets suggesting the eectiveness of proposed work.