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Hypervolume-based Multi-objective Bayesian Optimization with Student-t Processes | | Joachim van der Herten
; Ivo Couckuyt
; Tom Dhaene
; | | Date: |
1 Dec 2016 | | Abstract: | Student-$t$ processes have recently been proposed as an appealing alternative
non-parameteric function prior. They feature enhanced flexibility and
predictive variance. In this work the use of Student-$t$ processes are explored
for multi-objective Bayesian optimization. In particular, an analytical
expression for the hypervolume-based probability of improvement is developed
for independent Student-$t$ process priors of the objectives. Its effectiveness
is shown on a multi-objective optimization problem which is known to be
difficult with traditional Gaussian processes. | | Source: | arXiv, 1612.0393 | | Services: | Forum | Review | PDF | Favorites | |
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