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WWW
2005
ACM
15 years 10 months ago
Gimme' the context: context-driven automatic semantic annotation with C-PANKOW
Without the proliferation of formal semantic annotations, the Semantic Web is certainly doomed to failure. In earlier work we presented a new paradigm to avoid this: the 'Sel...
Günter Ladwig, Philipp Cimiano, Steffen Staab
IJCAI
2003
14 years 11 months ago
Bayesian Information Extraction Network
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Leonid Peshkin, Avi Pfeffer
EMNLP
2010
14 years 7 months ago
The Necessity of Combining Adaptation Methods
Problems stemming from domain adaptation continue to plague the statistical natural language processing community. There has been continuing work trying to find general purpose al...
Ming-Wei Chang, Michael Connor, Dan Roth
ICCPOL
2009
Springer
14 years 7 months ago
A Simple and Efficient Model Pruning Method for Conditional Random Fields
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Hai Zhao, Chunyu Kit
ICASSP
2011
IEEE
14 years 1 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...