Projective Preferential Bayesian Optimization
Loading...
Access rights
openAccess
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Date
2020-11-21
Major/Subject
Mcode
Degree programme
Language
en
Pages
9
6840-6848
6840-6848
Series
37th International Conference on Machine Learning, ICML 2020, Proceedings of Machine Learning Research
Abstract
Bayesian optimization is an effective method for finding extrema of a black-box function. We propose a new type of Bayesian optimization for learning user preferences in high-dimensional spaces. The central assumption is that the underlying objective function cannot be evaluated directly, but instead a minimizer along a projection can be queried, which we call a projective preferential query. The form of the query allows for feedback that is natural for a human to give, and which enables interaction. This is demonstrated in a user experiment in which the user feedback comes in the form of optimal position and orientation of a molecule adsorbing to a surface. We demonstrate that our framework is able to find a global minimum of a high-dimensional black-box function, which is an infeasible task for existing preferential Bayesian optimization frameworks that are based on pairwise comparisons.Description
Keywords
human-in-the-loop machine learning, gaussian process, preference learning, Bayesian optimization, Bayesian methods, machine learning, expert elicitation
Other note
Citation
Mikkola, P, Todorovic, M, Järvi, J, Rinke, P & Kaski, S 2020, Projective Preferential Bayesian Optimization . in 37th International Conference on Machine Learning, ICML 2020 . Proceedings of Machine Learning Research, International Machine Learning Society, pp. 6840-6848, International Conference on Machine Learning, Vienna, Austria, 12/07/2020 . < http://proceedings.mlr.press/v119/mikkola20a.html >