Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness

@inproceedings{Munos2011OptimisticOO,
  title={Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness},
  author={R{\'e}mi Munos},
  booktitle={NIPS},
  year={2011}
}
We consider a global optimization problem of a deterministic function f in a semimetric space, given a finite budget of n evaluations. The function f is assumed to be locally smooth (around one of its global maxima) with respect to a semi-metric l. We describe two algorithms based on optimistic exploration that use a hierarchical partitioning of the space at all scales. A first contribution is an algorithm, DOO, that requires the knowledge of l. We report a finite-sample performance bound in… CONTINUE READING
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