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Mark Mcleod

2 accepted papers

2018

Fast Information-theoretic Bayesian Optimisation

ICML 2018oral

Information-theoretic Bayesian optimisation techniques have demonstrated state-of-the-art performance in tackling important global optimisation problems. However, current information-theoretic approaches require many approximations in implementation, introduce often-prohibitive computational overhea…

2018

Optimization, fast and slow: optimally switching between local and Bayesian optimization

ICML 2018oral

We develop the first Bayesian Optimization algorithm, BLOSSOM, which selects between multiple alternative acquisition functions and traditional local optimization at each step. This is combined with a novel stopping condition based on expected regret. This pairing allows us to obtain the best charac…