Hierarchical HMM (HHMM) parsers make promising cognitive models: while they use a bounded model of working memory and pursue incremental hypotheses in parallel, they still achieve...
Stephen Wu, Asaf Bachrach, Carlos Cardenas, Willia...
To study PP attachment disambiguation as a benchmark for empirical methods in natural language processing it has often been reduced to a binary decision problem (between verb or n...
In this paper, we propose a novel method for semi-supervised learning of nonprojective log-linear dependency parsers using directly expressed linguistic prior knowledge (e.g. a no...
Background: Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propo...
Because English is a low morphology language, current statistical parsers tend to ignore morphology and accept some level of redundancy. This paper investigates how costly such re...
Matthew Honnibal, Jonathan K. Kummerfeld, James R....