The ICON challenge on algorithm selection

Lars Kotthoff; Barry Hurley; Barry O'Sullivan

doi:10.1609/aimag.v38i2.2722

The ICON challenge on algorithm selection

Lars Kotthoff
, Barry Hurley
, Barry O'Sullivan

University of British Columbia

Research output: Contribution to journal › Article › peer-review

Abstract

Algorithm selection is of increasing practical relevance in a variety of applications. Many approaches have been proposed in the literature, but their evaluations are often not comparable, making it hard to judge which approaches work best. The ICON Challenge on Algorithm Selection objectively evaluated many prominent approaches from the literature, making them directly comparable for the first time. The results show that there is still room for improvement, even for the very best approaches.

Original language	English
Pages (from-to)	91-93
Number of pages	3
Journal	AI Magazine
Volume	38
Issue number	2
DOIs	https://doi.org/10.1609/aimag.v38i2.2722
Publication status	Published - 1 Jun 2017

UCC Futures

Artificial Intelligence and Data Analytics

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10.1609/aimag.v38i2.2722

https://hdl.handle.net/10468/5057Licence: CC BY-NC-ND

Cite this

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title = "The ICON challenge on algorithm selection",

abstract = "Algorithm selection is of increasing practical relevance in a variety of applications. Many approaches have been proposed in the literature, but their evaluations are often not comparable, making it hard to judge which approaches work best. The ICON Challenge on Algorithm Selection objectively evaluated many prominent approaches from the literature, making them directly comparable for the first time. The results show that there is still room for improvement, even for the very best approaches.",

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The ICON challenge on algorithm selection

Abstract

UCC Futures

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