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10

ICML
2005
IEEE

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Preference learning with Gaussian processes

14 years 5 months ago

Preference learning with Gaussian processes

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In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relations in the Bayesian framework. The generalized formulation is also applicable to tackle many multiclass problems. The overall approach has the advantages of Bayesian methods for model selection and probabilistic prediction. Experimental results compared against the constraint classification approach on several benchmark datasets verify the usefulness of this algorithm.

Wei Chu, Zoubin Ghahramani

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Added	17 Nov 2009
Updated	17 Nov 2009
Type	Conference
Year	2005
Where	ICML
Authors	Wei Chu, Zoubin Ghahramani

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