TY  - CONF
AU  - Isabelle Guyon
AU  - Kristin Bennett
AU  - Gavin Cawley
AU  - Hugo Jair Escalante
AU  - Sergio Escalera
AU  - Tin Kam Ho
AU  - Nuria Macia
AU  - Bisakha Ray
AU  - Mehreen Saeed
AU  - Alexander Statnikov
AU  - Evelyne Viegas
A2  - ICML
PY  - 2015//
TI  - AutoML Challenge 2015: Design and First Results
BT  - 32nd International Conference on Machine Learning, ICML workshop, JMLR proceedings ICML15
SP  - 1
EP  - 8
KW  - AutoML Challenge
KW  - machine learning
KW  - model selection
KW  - meta-learning
KW  - repre- sentation learning
KW  - active learning
N2  - ChaLearn is organizing the Automatic Machine Learning (AutoML) contest 2015, which challenges participants to solve classication 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 diculty are introduced throughout the six rounds of the challenge. (Participants canenter the competition in any round.) The rounds alternate phases in which learners are tested on datasets participants have not seen (AutoML), and phases in which participants have limited time to tweak their algorithms on those datasets to improve performance (Tweakathon). 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: http://codalab.org/AutoML.
UR  - http://jmlr.org/proceedings/papers/v37
UR  - http://dx.doi.org/10.1109/IJCNN.2015.7280767
N1  - HuPBA;MILAB
ID  - Isabelle Guyon2015
ER  -