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ACL
2006
13 years 9 months ago
Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches
Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing me...
Yuya Unno, Takashi Ninomiya, Yusuke Miyao, Jun-ich...
HUMO
2007
Springer
14 years 1 months ago
Boosted Multiple Deformable Trees for Parsing Human Poses
Tree-structured models have been widely used for human pose estimation, in either 2D or 3D. While such models allow efficient learning and inference, they fail to capture additiona...
Yang Wang 0003, Greg Mori
TSD
2007
Springer
14 years 1 months ago
Accurate Unlexicalized Parsing for Modern Hebrew
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...
Reut Tsarfaty, Khalil Sima'an
JMLR
2010
143views more  JMLR 2010»
13 years 2 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
NLP
2000
13 years 11 months ago
Monte-Carlo Sampling for NP-Hard Maximization Problems in the Framework of Weighted Parsing
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...
Jean-Cédric Chappelier, Martin Rajman