Dependency parsing is instrumental in NLP applications, with recent examples in information extraction (Wu and Weld, 2010), word embeddings (Levy and Goldberg, 2014), and opinion mining (Almeida et al., 2015).
every other aspect of the parser -feature set, pruning algorithm, cost-augmented MIRA training (Crammer et al., 2006) etc., is kept fixed but our algorithms replace the inference algorithms: Chu-Liu- Edmonds ((Edmonds, 1967), first order) and dual-decomposition (higher order).