=Paper=
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|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-2360/paper2Keynote.pdf
|volume=Vol-2360
|dblpUrl=https://dblp.org/rec/conf/ecir/Lindauer19
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==None==
<pdf width="1500px">https://ceur-ws.org/Vol-2360/paper2Keynote.pdf</pdf>
<pre>
                                 Automated Algorithm Selection –Predict which
                                         algorithm to use! (Keynote)

                                                                       Marius Lindauer

                                             University of Freiburg – Automated Algorithm Design – Germany

                                                     lindauer@informatik.uni-freiburg.de



                                      Abstract. To achieve state-of-the-art performance, it is often crucial to select a
                                      suitable algorithm for a given problem instance. For example, what is the best
                                      search algorithm for a given instance of a search problem; or what is the best
                                      machine learning algorithm for a given dataset? By trying out many different
                                      algorithms on many problem instances, developers learn an intuitive mapping
                                      from some characteristics of a given problem instance (e.g., the number of fea-
                                      tures of a dataset) to a well-performing algorithm (e.g., random forest). The goal
                                      of automated algorithm selection is to learn from data, how to automatically se-
                                      lect a well-performing algorithm given such characteristics. In this talk, I will
                                      give an overview of the key ideas behind algorithm selection and different ap-
                                      proaches addressing this problem by using machine learning.




The 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in
Information Retrieval (AMIR), 14 April 2019, Cologne, Germany. Editors: Joeran
Beel and Lars Kotthoff. Co-located with the 41st European Conference on Infor-
mation Retrieval (ECIR). http://amir-workshop.org/

</pre>