Black-box optimization of noisy functions with unknown smoothness
Annual Conference on Neural Information Processing Systems, 2015.
We study the problem of black-box optimization of a function f of any dimension, given function evaluations perturbed by noise. The function is assumed to be locally smooth around one of its global optima, but this smoothness is unknown. Our contribution is an adaptive optimization algorithm, POO or parallel optimistic optimization, that ...More
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