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Predicting distributions with Linearizing Belief Networks
Yann N. Dauphin, David Grangier
Conditional belief networks introduce stochastic binary variables in neural networks. Contrary to a classical neural network, a belief network can predict more than the expected va…
EmoNets: Multimodal deep learning approaches for emotion recognition in video
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin +15
The task of the emotion recognition in the wild (EmotiW) Challenge is to assign one of seven emotions to short video clips extracted from Hollywood style movies. The videos depict…
Equilibrated adaptive learning rates for non-convex optimization
Yann N. Dauphin, Harm de Vries, Yoshua Bengio
Parameter-specific adaptive learning rate methods are computationally efficient ways to reduce the ill-conditioning problems encountered when training large deep networks. Followin…