Preference learning with Gaussian processes

Keywords

Computer science, Probabilistic logic, Artificial intelligence, Machine learning, Benchmark (surveying)

References

• Learning Preference Relations for Information RetrievalRalf Herbrich, Thore Graepel, Peter Bollmann-Sdorra — 1998
• Learning Subjective Functions with Large MarginsClaude-Nicolas Fiechter, Seth Rogers — 2000
• Learning with Kernels: support vector machines, regularization, optimization, and beyondBernhard Schölkopf, Alexander J. Smola — 2001
• Feature subset selection for learning preferences: a case studyAntonio Bahamonde, Gustavo F. Bayón, Jorge Díez — 2004
• Probability Estimates for Multi-class Classification by Pairwise CouplingTingfan Wu, Chih‐Jen Lin, Ruby C. Weng — 2003
• Bayesian Classification With Gaussian ProcessesChristopher K. I. Williams, David Barber — 1998
• Sparse On-Line Gaussian ProcessesLehel Csató, Manfred Opper — 2002
• Learning Preferences for Multiclass ProblemsFabio Aiolli, Alessandro Sperduti — 2004
• Fast Sparse Gaussian Process Methods: The Informative Vector MachineRalf Herbrich, Neil D. Lawrence, Matthias Seeger — 2002
• Prospects for PreferencesJon Doyle — 2004
• Log-Linear Models for Label RankingOfer Dekel, Yoram Singer, Christopher D. Manning — 2003
• Active learning of label ranking functionsKlaus Brinker — 2004
• Constraint Classification: A New Approach to Multiclass Classification and RankingSariel Har-Peled, Dan Roth, Dav Zimak — 2002
• Gaussian Processes for Ordinal RegressionChuWei, GhahramaniZoubin — 2005
• Probability Estimates for Multi-class Classification by Pairwise CouplingTingfan Wu, Chih‐Jen Lin, Ruby C. Weng — 2004
• Gaussian Processes for Ordinal RegressionWei Chu, Zoubin Ghahramani — 2005
• OHSUMED: an interactive retrieval evaluation and new large test collection for researchW. Hersh, C. Buckley, T. Leone — 1994
• Bayesian Methods for Backpropagation NetworksD. MacKay — 1996
• Pairwise Preference Learning and RankingJohannes Fürnkranz, E. Hullermeier — 2003
• Bayesian learning for neural networksRadford M. Neal — 1995

Cited by

• Preference Learning with Extreme ExamplesFei Wang, Bin Zhang, Ta‐Hsin Li — 2009
• Extensions of Gaussian processes for ranking: semi-supervised and active learningWei Chu, Zoubin Ghahramani — 2005
• Towards adaptive learning and inference : applications to hyperparameter tuning and astroparticle physicsRémi Bardenet — 2012
• Collaborative hyperparameter tuningRémi Bardenet, Mátyás Brendel, Bal zs K gl — 2013
• Multicriteria Models for Learning Ordinal Data: A Literature ReviewRicardo Sousa, Iryna Yevseyeva, Joaquim Pinto da Costa — 2013
• Semi-Supervised Learning by Mixed Label PropagationWei Tong, Rong Jin — 2007
• Efficient Transfer Learning Method for Automatic Hyperparameter TuningDani Yogatama, Gideon Mann — 2014
• Supervised learning as preference optimizationFabio Aiolli, Alessandro Sperduti — 2009
• Application of data mining in scheduling of single machine systemXiaonan Li — 2006
• Large-margin Weakly Supervised Dimensionality ReductionChang Xu, Dacheng Tao, Chao Xu — 2014
• Active Reward LearningChristian Daniel, Malte Viering, Jan Metz — 2014
• Interval Insensitive Loss for Ordinal ClassificationKostiantyn Antoniuk, Vojtěch Franc, Václav Hlaváč — 2014
• Surrogate-Assisted Evolutionary AlgorithmsIlya Loshchilov, SCHOENAUER, Marc, SEBAG, Michèle — 2013
• Achieving optimization invariance w.r.t. monotonous transformations of the objective function and orthogonal transformations of the representationIlya Loshchilov, Marc Schoenauer, Michèle Sébag — 2012
• Active reward learning with a novel acquisition functionChristian Daniel, Oliver Kroemer, Malte Viering — 2015
• Efficient Bayesian active learning and matrix modellingNeil Houlsby — 2014
• Kernel Principal Component Ranking: Robust Ranking on Noisy DataEvgeni Tsivtsivadze, Botond Cseke, Tom Heskes — 2009
• Exact Bayesian Pairwise Preference Learning and Inference on the Uniform Convex PolytopeScott Sanner, Ehsan Abbasnejad — 2011
• Preference learning with evolutionary Multivariate Adaptive Regression Spline modelMohamed Abou-Zleikha, Noor Shaker, Mads Græsbøll Christensen — 2015
• Learning Preferences with Kernel-Based MethodsEvgeni Tsivtsivadze — 2009

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