| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 412891 | Neurocomputing | 2010 | 9 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Adriana Birlutiu, Perry Groot, Tom Heskes,