Dual Decomposition

Via an oracle experiment, we show that the upper bound on accuracy of a CCG parser is significantly lowered when its search space is pruned using a supertagger, though the …...

Dual decomposition has been recently pro- posed as a way of combining complemen- tary models, with a boost in predictive power. However, in cases where lightweight decom- positions are not …...

We propose an algorithm to find the best path through an intersection of arbitrarily many weighted automata, without actually perform- ing the intersection. The algorithm is based on dual decomposition: …...

This paper addresses the extraction of event records from documents that describe multi- ple events. Specifically, we aim to identify the fields of information contained in a docu- ment and …...

Dependency parsing with high-order fea- tures results in a provably hard decoding problem. A lot of work has gone into developing powerful optimization meth- ods for solving these combinatorial prob- …...

In this paper we show how the task of syntactic parsing of non-segmented texts, including com- pound recognition, can be represented as constraints between phrase-structure parsers and CRF sequence labellers. …...

We describe a novel max-margin learn- ing approach to optimize non-linear perfor- mance measures for distantly-supervised re- lation extraction models. Our approach can be generally used to learn latent variable …...

AbstractUnsupervised dependency parsing aims to learn a dependency parser from unannotated sentences. Existing work focuses on either learning generative models using the expectation-maximization algorithm and its variants, or learning discriminative …...