Challenges in representation learning: A report on three machine learning contests

被引:332
|
作者
Goodfellow, Ian J. [1 ]
Erhan, Dumitru [2 ]
Carrier, Pierre Luc [1 ]
Courville, Aaron [1 ]
Mirza, Mehdi [1 ]
Hamner, Ben [3 ]
Cukierski, Will [3 ]
Tang, Yichuan [4 ]
Thaler, David
Lee, Dong-Hyun [5 ]
Zhou, Yingbo [6 ]
Ramaiah, Chetan [6 ]
Feng, Fangxiang [7 ]
Li, Ruifan [7 ]
Wang, Xiaojie [7 ]
Athanasakis, Dimitris [8 ]
Shawe-Taylor, John [8 ]
Milakov, Maxim
Park, John
Ionescu, Radu [9 ]
Popescu, Marius [9 ]
Grozea, Cristian [10 ]
Bergstra, James [11 ]
Xie, Jingjing [7 ]
Romaszko, Lukasz
Xu, Bing [7 ]
Chuang, Zhang [7 ]
Bengio, Yoshua [1 ]
机构
[1] Univ Montreal, Montreal, PQ H3T 1N8, Canada
[2] Google, Venice, CA 90291 USA
[3] Kaggle, Chicago, IL USA
[4] Univ Toronto, Toronto, ON M5S 1A1, Canada
[5] Nangman Comp, Seoul, South Korea
[6] SUNY Buffalo, Buffalo, NY 14260 USA
[7] Beijing Univ Posts & Telecommun, Beijing, Peoples R China
[8] UCL, London WC1E 6BT, England
[9] Univ Bucharest, Bucharest, Romania
[10] VICOM, Singapore, Singapore
[11] Univ Waterloo, Waterloo, ON N2L 3G1, Canada
关键词
Representation learning; Competition; Dataset;
D O I
10.1016/j.neunet.2014.09.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The ICML 2013 Workshop on Challenges in Representation Learning(1) focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions. (C) 2014 Elsevier Ltd. All rights reserved.
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页码:59 / 63
页数:5
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