Making Rational Decisions Using Adaptive Utility Elicitation
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Constraint Classification: A New Approach to Multiclass Classification
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Visual exploration and incremental utility elicitation
Eighteenth national conference on Artificial intelligence
A family of algorithms for approximate bayesian inference
A family of algorithms for approximate bayesian inference
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Task clustering and gating for bayesian multitask learning
The Journal of Machine Learning Research
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Learning Multiple Tasks with Kernel Methods
The Journal of Machine Learning Research
Preference learning with Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning Gaussian processes from multiple tasks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Multi-Task Learning for Classification with Dirichlet Process Priors
The Journal of Machine Learning Research
Expectation-propagation for the generative aspect model
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Expert Systems with Applications: An International Journal
Efficiently learning the preferences of people
Machine Learning
Learning output kernels for multi-task problems
Neurocomputing
Learning community-based preferences via dirichlet process mixtures of Gaussian processes
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Multi-task learning with one-class SVM
Neurocomputing
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We present an EM-algorithm for the problem of learning preferences with semiparametric models derived from Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data set and show that predictive results for sound quality perception of hearing-impaired subjects, in the context of pairwise comparison experiments, can be improved using a hierarchical model.