Sliced Recurrent Neural Networks

Understand

Recurrent neural networks have achieved great success in many NLP tasks.

• However, they have difficulty in parallelization because of the recurrent structure, so it takes much time to train RNNs.
• In this paper, we introduce sliced recurrent neural networks (SRNNs), which could be parallelized by slicing the sequences into many subsequences.
• SRNNs have the ability to obtain high-level information through multiple layers with few extra parameters.