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» Structural Correspondence Learning for Dependency Parsing
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NIPS
2001
13 years 9 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning
EMNLP
2009
13 years 5 months ago
Parser Adaptation and Projection with Quasi-Synchronous Grammar Features
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...
David A. Smith, Jason Eisner
CVPR
2011
IEEE
13 years 3 months ago
Learning Message-Passing Inference Machines for Structured Prediction
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Stephane Ross, Daniel Munoz, J. Andrew Bagnell
ECML
2003
Springer
14 years 25 days ago
Learning Context Free Grammars in the Limit Aided by the Sample Distribution
We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...
Yoav Seginer
ICCS
2001
Springer
14 years 1 days ago
Learning to Generate CGs from Domain Specific Sentences
Automatically generating Conceptual Graphs (CGs) [1] from natural language sentences is a difficult task in using CG as a semantic (knowledge) representation language for natural l...
Lei Zhang, Yong Yu