149 citations · 226 across the 29 of their papers we have counts for
4 papers · 1 filter
Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition
Yong Jiang, Wenjuan Han, Kewei Tu
Unsupervised dependency parsing aims to learn a dependency parser from unannotated sentences. Existing work focuses on either learning generative models using the expectation-maxim…
CRF Autoencoder for Unsupervised Dependency Parsing
Jiong Cai, Yong Jiang, Kewei Tu
Unsupervised dependency parsing, which tries to discover linguistic dependency structures from unannotated data, is a very challenging task. Almost all previous work on this task f…
Dependency Grammar Induction with Neural Lexicalization and Big Training Data
Wenjuan Han, Yong Jiang, Kewei Tu
We study the impact of big models (in terms of the degree of lexicalization) and big data (in terms of the training corpus size) on dependency grammar induction. We experimented wi…
Maximum A Posteriori Inference in Sum-Product Networks
Jun Mei, Yong Jiang, Kewei Tu
Sum-product networks (SPNs) are a class of probabilistic graphical models that allow tractable marginal inference. However, the maximum a posteriori (MAP) inference in SPNs is NP-h…