Name
Abstract | ||
|---|---|---|
In this work, we present the first results for neuralizing an Unsupervised Hidden Markov Model. We evaluate our approach on tag in- duction. Our approach outperforms existing generative models and is competitive with the state-of-the-art though with a simpler model easily extended to include additional context. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.18653/v1/W16-5907 | SPNLP@EMNLP |
DocType | Volume | Citations |
Conference | abs/1609.09007 | 5 |
PageRank | References | Authors |
0.45 | 20 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ke M. Tran | 1 | 21 | 2.58 |
| Yonatan Bisk | 2 | 196 | 17.54 |
| Ashish Vaswani | 3 | 901 | 32.81 |
| Daniel Marcu | 4 | 5696 | 415.42 |
| Kevin Knight | 5 | 5096 | 462.44 |