Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
Pre-symptomatic drought stress prediction is of great relevance in precision plant protection, ultimately helping to meet the challenge of “How to feed a hungry world?”. Unfor...
Kristian Kersting, Zhao Xu, Mirwaes Wahabzada, Chr...