Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces

arXiv: Optimization and Control, 2019.

Cited by: 0|Views36
EI

Abstract:

We present a new algorithm ASEBO for conducting optimization of high-dimensional blackbox functions. ASEBO adapts to the geometry of the function and learns optimal sets of sensing directions, which are used to probe it, on-the-fly. It addresses the exploration-exploitation trade-off of blackbox optimization, where each single function qu...More

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