Many structured information extraction tasks employ collective graphical models that capture interinstance associativity by coupling them with various clique potentials. We propos...
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...
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...
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...