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Found 6 papers, 3 papers with code
Hyperparameter Selection in Continual Learning
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 of the data at the same time.
Data-driven Prior Learning for Bayesian Optimisation
We replace this assumption with a weaker one only requiring the shape of the optimisation landscape to be similar, and analyse the recent method Prior Learning for Bayesian Optimisation - PLeBO - in this setting.
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation
We introduce ordered transfer hyperparameter optimisation (OTHPO), a version of transfer learning for hyperparameter optimisation (HPO) where the tasks follow a sequential order.
Bayesian Optimisation Against Climate Change: Applications and Benchmarks
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 available.
Bayesian Optimisation for Active Monitoring of Air Pollution
Air pollution is one of the leading causes of mortality globally, resulting in millions of deaths each year.
Optimising Placement of Pollution Sensors in Windy Environments
Air pollution is one of the most important causes of mortality in the world.
