Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
A method for using monotonicity information in multivariate Gaussian process regression and classification is proposed. Monotonicity information is introduced with virtual derivat...
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...