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» Learning Flexible Features for Conditional Random Fields
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SIGIR
2009
ACM
15 years 4 months ago
Extracting structured information from user queries with semi-supervised conditional random fields
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
Xiao Li, Ye-Yi Wang, Alex Acero
JMLR
2008
230views more  JMLR 2008»
14 years 9 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
68
Voted
JMLR
2010
160views more  JMLR 2010»
14 years 4 months ago
Neural conditional random fields
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
Trinh Minh Tri Do, Thierry Artières
ICML
2004
IEEE
15 years 10 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
99
Voted
ICML
2005
IEEE
15 years 10 months ago
2D Conditional Random Fields for Web information extraction
The Web contains an abundance of useful semistructured information about real world objects, and our empirical study shows that strong sequence characteristics exist for Web infor...
Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Y...