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- Université de MontréalCA18 papers
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- École de Technologie SupérieureCA6 papers
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20 papers · 1 filter
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho +1
In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism,…
End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results
Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho +1
We replace the Hidden Markov Model (HMM) which is traditionally used in in continuous speech recognition with a bi-directional recurrent neural network encoder coupled to a recurre…
FitNets: Hints for Thin Deep Nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou +3
While depth tends to improve network performances, it also makes gradient-based training more difficult since deeper networks tend to be more non-linear. The recently proposed know…
Robust Cooperative Spectrum Sensing Scheduling Optimization in Multi-Channel Dynamic Spectrum Access Networks
Chun-Hao Liu, Arash Azarfar, Jean-Francois Frigon +2
Dynamic spectrum access (DSA) enables secondary networks to find and efficiently exploit spectrum opportunities. A key factor to design a DSA network is the spectrum sensing algori…
Not All Neural Embeddings are Born Equal
Felix Hill, KyungHyun Cho, Sebastien Jean +2
Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation…
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau +1
Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of a…