Pairwise Judgements and Absolute Ratings with Gaussian Process Priors

AbstractIn 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.
TypeTechnical report
Year2014    Month January
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing