Frédéric Suard

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A common approach for classifying shock graphs is to use a dissimilarity measure on graphs and a distance based classifier. In this paper, we propose the use of kernel functions for data mining problems on shock graphs. The first contribution of the paper is to extend the class of graph kernel by proposing kernels based on bag of paths. Then, we propose a(More)
This paper presents a method for object categorization. This problem is difficult and can be solved by combining different information sources such as shape or appearance. In this paper, we aim at performing object recognition by mixing kernels obtained from different cues. Our method is based on two complementary descriptions of an object. First, we(More)
The Doubly Regularized SVM (DrSVM) is an extension of SVM using a mixture of L2 and L1 norm penalties. This kind of penalty, sometimes referred as the elastic net, allows to perform variable selection while taking into account correlations between variables. Introduced by Wang [1], an ecient algorithm to compute the whole DrSVM solution path has been(More)
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