LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

NeurIPS 2016 Xiang LiTao QinJian YangTie-Yan Liu

Recurrent neural networks (RNNs) have achieved state-of-the-art performances in many natural language processing tasks, such as language modeling and machine translation. However, when the vocabulary is large, the RNN model will become very big (e.g., possibly beyond the memory capacity of a GPU device) and its training will become very inefficient... (read more)

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