12 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CL2017
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
Dung Thai, Shikhar Murty, Trapit Bansal +3
In textual information extraction and other sequence labeling tasks it is now common to use recurrent neural networks (such as LSTM) to form rich embedded representations of long-t…
cs.LG2015
Bethe Learning of Conditional Random Fields via MAP Decoding
Kui Tang, Nicholas Ruozzi, David Belanger +1
Many machine learning tasks can be formulated in terms of predicting structured outputs. In frameworks such as the structured support vector machine (SVM-Struct) and the structured…
stat.ML2015★ 12 cited
A Linear Dynamical System Model for Text
David Belanger, Sham Kakade
Low dimensional representations of words allow accurate NLP models to be trained on limited annotated data. While most representations ignore words' local context, a natural way to…