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4 months ago
Challenges in Representation Learning: A report on three machine learning contests
Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron Courville; Mehdi Mirza; Ben Hamner; Will Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; Fangxiang Feng; Ruifan Li; Xiaojie Wang; Dimitris Athanasakis; John Shawe-Taylor; Maxim Milakov; John Park; Radu Ionescu; Marius Popescu; Cristian Grozea; James Bergstra; Jingjing Xie; Lukasz Romaszko; Bing Xu; Zhang Chuang; Yoshua Bengio

Abstract
The ICML 2013 Workshop on Challenges in Representation Learning 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.
Code Repositories
hemanshanand/Facial-Expression-Recognition
tf
Mentioned in GitHub
leorrose/Facial-Expression-Recognition
tf
Mentioned in GitHub
Conero007/Emotion-Detection-Pytorch
pytorch
Mentioned in GitHub
chinhau-lim/fer2013
tf
Mentioned in GitHub
chinhau-lim/fer_2013
tf
Mentioned in GitHub
NJNischal/Facial-Expression-Recognition-with-CNNs
tf
Mentioned in GitHub
jannine92/supervised_emotion_recognition
tf
Mentioned in GitHub
oellop/facial_expression
tf
Mentioned in GitHub
leorrose/Social-Network-Facial-Expression-Recognition
tf
Mentioned in GitHub
justinshenk/fer
tf
Mentioned in GitHub
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| facial-expression-recognition-on-fer2013 | Local Learning BOW | Accuracy: 67.48 |
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