A Short Tutorial on the Marginalized Graph Kernel

In the framework of the marginalized graph kernel algorithm [Kashima, H., Tsuda, K., & Inokuchi, A. (2003). Marginalized kernels between labeled graphs. In Proceedings of the 20th international conference on machine learning (ICML-03) (pp. 321-328).], the similarity between two graphs is computed as the expectation of individual similarities of pairs of paths generated from a random walk process.