26 citations · 63 across the 3 of their papers we have counts for
3 papers
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod, Michael A. Osborne, Stephen J. Roberts
We develop the first Bayesian Optimization algorithm, BLOSSOM, which selects between multiple alternative acquisition functions and traditional local optimization at each step. Thi…
Fast Information-theoretic Bayesian Optimisation
Binxin Ru, Mark McLeod, Diego Granziol +1
Information-theoretic Bayesian optimisation techniques have demonstrated state-of-the-art performance in tackling important global optimisation problems. However, current informati…
Practical Bayesian Optimization for Variable Cost Objectives
Mark McLeod, Michael A. Osborne, Stephen J. Roberts
We propose a novel Bayesian Optimization approach for black-box functions with an environmental variable whose value determines the tradeoff between evaluation cost and the fidelit…