20 citations · 24 across the 5 of their papers we have counts for
5 papers · 1 filter
GIBBON: General-purpose Information-Based Bayesian OptimisatioN
Henry B. Moss, David S. Leslie, Javier Gonzalez +1
This paper describes a general-purpose extension of max-value entropy search, a popular approach for Bayesian Optimisation (BO). A novel approximation is proposed for the informati…
BOSS: Bayesian Optimization over String Spaces
Henry B. Moss, Daniel Beck, Javier Gonzalez +2
This article develops a Bayesian optimization (BO) method which acts directly over raw strings, proposing the first uses of string kernels and genetic algorithms within BO loops. R…
BOSH: Bayesian Optimization by Sampling Hierarchically
Henry B. Moss, David S. Leslie, Paul Rayson
Deployments of Bayesian Optimization (BO) for functions with stochastic evaluations, such as parameter tuning via cross validation and simulation optimization, typically optimize a…
MUMBO: MUlti-task Max-value Bayesian Optimization
Henry B. Moss, David S. Leslie, Paul Rayson
We propose MUMBO, the first high-performing yet computationally efficient acquisition function for multi-task Bayesian optimization. Here, the challenge is to perform efficient opt…
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
Henry B. Moss, Andrew Moore, David S. Leslie +1
We present FIESTA, a model selection approach that significantly reduces the computational resources required to reliably identify state-of-the-art performance from large collectio…