Extensions of Gaussian processes for ranking: semi-supervised and active learning
Unlabelled examples in supervised learning tasks can be optimally exploited using semi-supervised methods and active learning. We focus on ranking learning from pairwise instance preference to discuss these important extensions, semi-supervised learning and active learning, in the probabilistic framework of Gaussian processes. Numerical experiments demonstrate the capacities of these techniques.