Maximum Likelihood for Gaussians on Graphs

摘要

We show that extending the Gaussian distribution to the domain of graphs corresponds to truncated Gaussian distributions in Euclidean spaces. Based on this observation, we derive a maximum likelihood method for estimating the parameters of the Gaussian on graphs. In conjunction with a naive Bayes classifier, we applied the proposed approach to image classification.