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ICML
2004
IEEE
15 years 10 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
ICASSP
2010
IEEE
14 years 10 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
EMNLP
2009
14 years 7 months ago
Natural Language Generation with Tree Conditional Random Fields
This paper presents an effective method for generating natural language sentences from their underlying meaning representations. The method is built on top of a hybrid tree repres...
Wei Lu, Hwee Tou Ng, Wee Sun Lee
ACL
2001
14 years 11 months ago
A Syntax-based Statistical Translation Model
We present a syntax-based statistical translation model. Our model transforms a source-language parse tree into a target-language string by applying stochastic operations at each ...
Kenji Yamada, Kevin Knight
HEURISTICS
2006
95views more  HEURISTICS 2006»
14 years 10 months ago
Hard and soft constraints for reasoning about qualitative conditional preferences
Many real life optimization problems are defined in terms of both hard and soft constraints, and qualitative conditional preferences. However, there is as yet no single framework f...
Carmel Domshlak, Steven David Prestwich, Francesca...