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ACL
2008
13 years 11 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
EMNLP
2009
13 years 7 months ago
Supervised and Unsupervised Methods in Employing Discourse Relations for Improving Opinion Polarity Classification
This work investigates design choices in modeling a discourse scheme for improving opinion polarity classification. For this, two diverse global inference paradigms are used: a su...
Swapna Somasundaran, Galileo Namata, Janyce Wiebe,...
JMLR
2010
102views more  JMLR 2010»
13 years 4 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
ICDM
2010
IEEE
193views Data Mining» more  ICDM 2010»
13 years 7 months ago
Supervised Link Prediction Using Multiple Sources
Link prediction is a fundamental problem in social network analysis and modern-day commercial applications such as Facebook and Myspace. Most existing research approaches this pro...
Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S....
NAACL
2010
13 years 7 months ago
Minimally-Supervised Extraction of Entities from Text Advertisements
Extraction of entities from ad creatives is an important problem that can benefit many computational advertising tasks. Supervised and semi-supervised solutions rely on labeled da...
Sameer Singh, Dustin Hillard, Chris Leggetter