Papers with large-scale sentiment analysis

1 papers
Sliced Recurrent Neural Networks (C18-1)

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Challenge: Recurrent neural networks have difficulty in parallelization because of their recurrent structure.
Approach: They propose sliced recurrent neural networks (SRNNs) which can be parallelized by slicing sequences into many subsequences.
Outcome: The proposed recurrent neural networks perform better than standard RNNs on six large-scale sentiment analysis datasets.

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