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JMLR
2010
105views more  JMLR 2010»
8 years 6 months ago
Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials
Many structured information extraction tasks employ collective graphical models that capture interinstance associativity by coupling them with various clique potentials. We propos...
Rahul Gupta, Sunita Sarawagi, Ajit A. Diwan
NIPS
2001
9 years 1 months ago
The g Factor: Relating Distributions on Features to Distributions on Images
We describe the g-factor which relates probability distributions on image features to distributions on the images themselves. The g-factor depends only on our choice of features a...
James M. Coughlan, Alan L. Yuille
ICML
2007
IEEE
10 years 20 days ago
Efficient inference with cardinality-based clique potentials
Many collective labeling tasks require inference on graphical models where the clique potentials depend only on the number of nodes that get a particular label. We design efficien...
Rahul Gupta, Ajit A. Diwan, Sunita Sarawagi
ECCV
2006
Springer
10 years 1 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
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