Publication Details

A Survey of Methods for Automated Algorithm Configuration (Extended Abstract)

authored by
Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
Abstract

Algorithm configuration (AC) is concerned with the automated search of the most suitable parameter configuration of a parametrized algorithm. There are currently a wide variety of AC problem variants and methods proposed in the literature. Existing reviews do not take into account all derivatives of the AC problem, nor do they offer a complete classification scheme. To this end, we introduce taxonomies to describe the AC problem and features of configuration methods, respectively. Existing AC literature is classified and characterized by the provided taxonomies.

Organisation(s)
Machine Learning Section
Institute of Artificial Intelligence
External Organisation(s)
Bielefeld University
Paderborn University
Ludwig-Maximilians-Universität München (LMU)
Munich Center for Machine Learning (MCML)
Type
Conference contribution
Pages
6964-6968
No. of pages
5
Publication date
2023
Publication status
Published
Peer reviewed
Yes
ASJC Scopus subject areas
Artificial Intelligence
Electronic version(s)
https://doi.org/10.24963/ijcai.2023/791 (Access: Open)