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Brandt, Jasmin; Schede, Elias; Haddenhorst, Björn ORCID logoORCID: https://orcid.org/0000-0002-4023-6646; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 and Tierney, Kevin (7. February 2023): AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. AAAI Conference on Artificial Intelligence, Washington, DC, USA, February, 2023. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 37, No. 10 pp. 12355-12363

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Abstract

We study the algorithm configuration (AC) problem, in which one seeks to find an optimal parameter configuration of a given target algorithm in an automated way. Although this field of research has experienced much progress recently regarding approaches satisfying strong theoretical guarantees, there is still a gap between the practical performance of these approaches and the heuristic state-of-the-art approaches. Recently, there has been significant progress in designing AC approaches that satisfy strong theoretical guarantees. However, a significant gap still remains between the practical performance of these approaches and state-of-the-art heuristic methods. To this end, we introduce AC-Band, a general approach for the AC problem based on multi-armed bandits that provides theoretical guarantees while exhibiting strong practical performance. We show that AC-Band requires significantly less computation time than other AC approaches providing theoretical guarantees while still yielding high-quality configurations.

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