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Bai and Hancock recently proposed a novel information theoretic kernel for graphs, namely the Jensen-Shannon graph kernel. One drawback of their approach is that it cannot be applied to either attributed or labeled graphs. In this paper, we aim to define a new Jensen-Shannon diffusion kernel for attributed graphs. We commence by using a tree-index based label strengthening method on an attributed...
In recent work we have shown how to use the von Neumann entropy to construct a Jensen-Shannon kernel on graphs. The kernel is defined as the difference in entropies between a product graph and the separate graphs being compared. To develop this graph kernel further, in this paper we explore how to render the computation of the Jensen-Shannon kernel more efficient by using the information functionals...
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