Design of the 2015 ChaLearn AutoML challenge

Isabelle Guyon; Gavin Cawley; Kristin Bennett; Hugo Jair Escalente; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Mehreen Saeed; Alexander Statnikov; Evelyne Viegas

doi:10.1109/IJCNN.2015.7280767

Design of the 2015 ChaLearn AutoML challenge

Isabelle Guyon (Lead Author), Gavin Cawley, Kristin Bennett, Hugo Jair Escalente, Sergio Escalera, Tin Kam Ho, Nuria Macia, Bisakha Ray, Mehreen Saeed, Alexander Statnikov, Evelyne Viegas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

68 Citations (Scopus)

Abstract

ChaLearn is organizing the Automatic Machine Learning (AutoML) contest for IJCNN 2015, which challenges participants to solve classification and regression problems without any human intervention. Participants' code is automatically run on the contest servers to train and test learning machines. However, there is no obligation to submit code; half of the prizes can be won by submitting prediction results only. Datasets of progressively increasing difficulty are introduced throughout the six rounds of the challenge. (Participants can enter the competition in any round.) The rounds alternate phases in which learners are tested on datasets participants have not seen, and phases in which participants have limited time to tweak their algorithms on those datasets to improve performance. This challenge will push the state of the art in fully automatic machine learning on a wide range of real-world problems. The platform will remain available beyond the termination of the challenge.

Original language	English
Title of host publication	Proceedings of International Joint Conference on Neural Networks (IJCNN)
Publisher	The Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	8
DOIs	https://doi.org/10.1109/IJCNN.2015.7280767
Publication status	Published - 12 Jul 2015

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10.1109/IJCNN.2015.7280767

Gavin Cawley
- G.Cawleyuea.acuk
- Data Science and AI - Member
- School of Computing Sciences - Senior Lecturer
- Centre for Ocean and Atmospheric Sciences - Member
- Computational Biology - Member
Person: Research Group Member, Academic, Teaching & Research

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Guyon, I., Cawley, G., Bennett, K., Jair Escalente, H., Escalera, S., Ho, T. K., Macia, N., Ray, B., Saeed, M., Statnikov, A., & Viegas, E. (2015). Design of the 2015 ChaLearn AutoML challenge. In Proceedings of International Joint Conference on Neural Networks (IJCNN) The Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IJCNN.2015.7280767

Guyon, Isabelle ; Cawley, Gavin ; Bennett, Kristin ; Jair Escalente, Hugo ; Escalera, Sergio ; Ho, Tin Kam ; Macia, Nuria ; Ray, Bisakha ; Saeed, Mehreen ; Statnikov, Alexander ; Viegas, Evelyne. / Design of the 2015 ChaLearn AutoML challenge. Proceedings of International Joint Conference on Neural Networks (IJCNN). The Institute of Electrical and Electronics Engineers (IEEE), 2015.

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title = "Design of the 2015 ChaLearn AutoML challenge",

abstract = "ChaLearn is organizing the Automatic Machine Learning (AutoML) contest for IJCNN 2015, which challenges participants to solve classification and regression problems without any human intervention. Participants' code is automatically run on the contest servers to train and test learning machines. However, there is no obligation to submit code; half of the prizes can be won by submitting prediction results only. Datasets of progressively increasing difficulty are introduced throughout the six rounds of the challenge. (Participants can enter the competition in any round.) The rounds alternate phases in which learners are tested on datasets participants have not seen, and phases in which participants have limited time to tweak their algorithms on those datasets to improve performance. This challenge will push the state of the art in fully automatic machine learning on a wide range of real-world problems. The platform will remain available beyond the termination of the challenge.",

author = "Isabelle Guyon and Gavin Cawley and Kristin Bennett and {Jair Escalente}, Hugo and Sergio Escalera and Ho, {Tin Kam} and Nuria Macia and Bisakha Ray and Mehreen Saeed and Alexander Statnikov and Evelyne Viegas",

year = "2015",

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booktitle = "Proceedings of International Joint Conference on Neural Networks (IJCNN)",

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Design of the 2015 ChaLearn AutoML challenge. / Guyon, Isabelle (Lead Author); Cawley, Gavin; Bennett, Kristin; Jair Escalente, Hugo; Escalera, Sergio; Ho, Tin Kam; Macia, Nuria; Ray, Bisakha; Saeed, Mehreen; Statnikov, Alexander; Viegas, Evelyne.

Proceedings of International Joint Conference on Neural Networks (IJCNN). The Institute of Electrical and Electronics Engineers (IEEE), 2015.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Design of the 2015 ChaLearn AutoML challenge

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