54 citations · 55 across the 3 of their papers we have counts for
4 papers
Depth Growing for Neural Machine Translation
Lijun Wu, Yiren Wang, Yingce Xia +5
While very deep neural networks have shown effectiveness for computer vision and text classification applications, how to increase the network depth of neural machine translation (…
Learning What Data to Learn
Yang Fan, Fei Tian, Tao Qin +2
Machine learning is essentially the sciences of playing with data. An adaptive data selection strategy, enabling to dynamically choose different data at various training stages, ca…
Sentence Level Recurrent Topic Model: Letting Topics Speak for Themselves
Fei Tian, Bin Gao, Di He +1
We propose Sentence Level Recurrent Topic Model (SLRTM), a new topic model that assumes the generation of each word within a sentence to depend on both the topic of the sentence an…
Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph
Fei Tian, Bin Gao, Enhong Chen +1
Word embedding, which refers to low-dimensional dense vector representations of natural words, has demonstrated its power in many natural language processing tasks. However, it may…