15 citations · 15 across the 1 of their papers we have counts for
5 papers
How Bayesian Should Bayesian Optimisation Be?
George De Ath, Richard Everson, Jonathan Fieldsend
Bayesian optimisation (BO) uses probabilistic surrogate models - usually Gaussian processes (GPs) - for the optimisation of expensive black-box functions. At each BO iteration, the…
What do you Mean? The Role of the Mean Function in Bayesian Optimisation
George De Ath, Jonathan E. Fieldsend, Richard M. Everson
Bayesian optimisation is a popular approach for optimising expensive black-box functions. The next location to be evaluated is selected via maximising an acquisition function that…
-shotgun: -greedy Batch Bayesian Optimisation
George De Ath, Richard M. Everson, Jonathan E. Fieldsend +1
Bayesian optimisation is a popular, surrogate model-based approach for optimising expensive black-box functions. Given a surrogate model, the next location to expensively evaluate…
Visual Object Tracking: The Initialisation Problem
George De Ath, Richard Everson
Model initialisation is an important component of object tracking. Tracking algorithms are generally provided with the first frame of a sequence and a bounding box (BB) indicating…
Part-based Tracking by Sampling
George De Ath, Richard M. Everson
We propose a novel part-based method for tracking an arbitrary object in challenging video sequences. The colour distribution of tracked image patches on the target object are repr…