We study the problem of combining the outcomes of several different classifiers in a way that provides a coherent inference that satisfies some constraints. In particular, we deve...
Many state-of-the-art statistical parsers for English can be viewed as Probabilistic Context-Free Grammars (PCFGs) acquired from treebanks consisting of phrase-structure trees enri...
In this paper we present a joint content selection and compression model for single-document summarization. The model operates over a phrase-based representation of the source doc...
We extend stochastic context-free grammars such that the probability of applying a production can depend on the length of the subword that is generated from the application and sho...
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...