| Abstract | In this report we shortly discuss preference learning using Gaussian Process priors with classic likelihoods. We then suggest and describe a new likelihood function for this task, applicable for both pairwise judgments and absolute ratings. The appendix contains relevant derivations required for parameter estimation and inference. |