F ourier transform of a positive finite measure. Hence the RFF is limited to a small range of simple kernel functions such as RBF kernel. KL divergence between the variational distribution and the true posterior over latent variable A . 2 Algorithm 1 The proposed GPSRF approach for semi-supervised object classification task. We provide an overview of the optimization process of GPSRF for object classification in Algorithm 1. ELBO defined in Eq. (7). The features of each node are bag-of-word representations of the corresponding publications.

Gaussian Processes (GPs) define distributions over functions and their generalization capabilities depend heavily on the choice of kernels.

F ourier transform of a positive finite measure. Hence the RFF is limited to a small range of simple kernel functions such as RBF kernel. KL divergence between the variational distribution and the true posterior over latent variable A . 2 Algorithm 1 The proposed GPSRF approach for semi-supervised object classification task. We provide an overview of the optimization process of GPSRF for object classification in Algorithm 1. ELBO defined in Eq. (7). The features of each node are bag-of-word representations of the corresponding publications.