Kernel Based Implicit Graph Regularization of Structured Objects

Francois-Xavier Dupe &
Seebastien Bougleux &
Luc Brun &
Olivier Lezoray &
Abder Elmoataz.

Weighted Graph regularization provides a rich framework which allow to regularize functions defined over the vertice of a weighted graph. Until now, such a framework has been only defined for real or multivalued functions hereby restricting the regularization framework to numerical objects. On the other hand, several kernels have been defined on structured objects such as strings or graphs. Using definite positive kernels, each original object is associated by the ``kernel trick'' to one element of an Hilbert space. This paper proposes to extend the weighted graph regularization framework to objects implicitly defined by their kernel hereby performing the regularization within the Hilbert space associated to the kernel. This work opens the door to the regularization of structured objects.