Abstract. This paper explores the use of initial Stochastic Context-Free Grammars (SCFG) obtained from a treebank corpus for the learning of SCFG by means of estimation algorithms....
The traditional mention-pair model for coreference resolution cannot capture information beyond mention pairs for both learning and testing. To deal with this problem, we present ...
Xiaofeng Yang, Jian Su, Jun Lang, Chew Lim Tan, Ti...
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of information not consi...
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...