We here present a method derived from the study of reproducing-kernel Hilbert spaces which takes advantage of the regular structure of the space of all graphs ...

the function is a globally smooth one over the graph topology. We then performed a set of experiments using the metagraph kernel. 4.1.1 Randomly Drawn ...

Dec 8, 2008 · Bayesian network score approximation using a metagraph kernel ; Benjamin Yackley. Department of Computer Science, University of New Mexico.

Found 1 papers, 0 papers with code. Date Published. Date Published Github Stars · Bayesian Network Score Approximation using a Metagraph Kernel · no code ...

Bayesian Network Score Approximation using a Metagraph Kernel ... Many interesting problems, including Bayesian network structure-search, can be cast in terms of ...

Abstract. In this paper we introduce two novel methods for performing. Bayesian network structure search that make use of Gaussian Process re- gression.

Bayesian network score approximation using a metagraph kernel. B Yackley, E Corona, T Lane. Advances in Neural Information Processing Systems 21, 2008. 10, 2008.

Bayesian network score approximation using a metagraph kernel. B Yackley, E Corona, T Lane. Advances in Neural Information Processing Systems 21, 2008. 10, 2008.

We prove here that the use of such a proxy is well-founded, as we can bound the smoothness of a commonly-used scoring function for Bayesian network structure ...