From this point of view, our work is closely related to the discriminative training methods for low-rank tensors in NLP (Cao and Khudanpur, 2014;Lei et al., 2014), while it can handle more complex ngram-to-ngram tasks, where the label y also has its embedding composed from basic word embeddings.
our model can capture the above work as special cases.