Learning inconsistent preferences with Gaussian processes
We revisit widely used preferential Gaussian processes (PGP) by Chu and Ghahramani [2005] and challenge their modelling assumption that imposes rankability of data items via latent utility function values. We propose a generalisation of PGP which can capture more expressive latent preferential struc...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2022
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