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This article describes the final solution of team monkeytyping, who finished in second place in the YouTube-8M video understanding challenge.
Bagging predictors
L. Breiman · 1996
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Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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L. Breiman · 1998
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Classifier chains for multi-label classification
J. Read, B. Pfahringer, G. Holmes, and E. Frank · 2009
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Feature-weighted linear stacking
J. Sill, G. Takács, L. Mackey, and D. Lin · 2009
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Temporal segmentation and activity classification from first-person sensing
E. H. Spriggs, F. De La Torre, and M. Hebert · 2009
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Ensemble methods: foundations and algorithms
Z.-H. Zhou · 2012
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Large-scale video classification with convolutional neural networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei · 2014
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Convolutional neural networks for sentence classification
Y. Kim · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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A deep interpretation of classifier chains
J. Read and J. Hollmén · 2014
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Activitynet: A large-scale video benchmark for human activity understanding
F. Caba Heilbron, V. Escorcia, B. Ghanem, and J. Carlos Niebles · 2015
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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
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Youtube-8m: A large-scale video classification benchmark
S. Abu-El-Haija, N. Kothari, J. Lee, P. Natsev, G. Toderici, B. Varadarajan, and S. Vijayanarasimhan · 2016
Later among the works it cites.
Attention pooling-based convolutional neural network for sentence modelling
M. J. Er, Y. Zhang, N. Wang, and M. Pratama · 2016
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Temporal segment networks: towards good practices for deep action recognition
L. Wang, Y. Xiong, Z. Wang, Y. Qiao, D. Lin, X. Tang, and L. Van Gool · 2016
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