Alors: An algorithm recommender system

摘要

Algorithm selection (AS), selecting the algorithm best suited for a particular problem instance, is acknowledged to be a key issue to make the best out of algorithm portfolios. This paper presents a collaborative filtering approach to AS. Collaborative filtering, popularized by the Netflix challenge, aims to recommend the items that a user will most probably like, based on the previous items she liked, and the items that have been liked by other users. As first noted by Stern et al. [47], algorithm selection can be formalized as a collaborative filtering problem, by considering that a problem instance “likes better“ the algorithms that achieve better performance on this particular instance.