4 papers
Hyperparameter Selection in Continual Learning
Thomas L. Lee, Sigrid Passano Hellan, Linus Ericsson +2
In continual learning (CL) -- where a learner trains on a stream of data -- standard hyperparameter optimisation (HPO) cannot be applied, as a learner does not have access to all o…
Data-driven Prior Learning for Bayesian Optimisation
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Transfer learning for Bayesian optimisation has generally assumed a strong similarity between optimisation tasks, with at least a subset having similar optimal inputs. This assumpt…
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation
Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet +2
We introduce ordered transfer hyperparameter optimisation (OTHPO), a version of transfer learning for hyperparameter optimisation (HPO) where the tasks follow a sequential order. U…
Bayesian Optimisation Against Climate Change: Applications and Benchmarks
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Bayesian optimisation is a powerful method for optimising black-box functions, popular in settings where the true function is expensive to evaluate and no gradient information is a…