Semi-supervised Structured Prediction with Neural CRF Autoencoder

EMNLP 2017 Xiao ZhangYong JiangHao PengKewei TuDan Goldwasser

In this paper we propose an end-to-end neural CRF autoencoder (NCRF-AE) model for semi-supervised learning of sequential structured prediction problems. Our NCRF-AE consists of two parts: an encoder which is a CRF model enhanced by deep neural networks, and a decoder which is a generative model trying to reconstruct the input... (read more)

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