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» A Markov random field model for term dependencies
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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
ICIAP
2007
ACM
14 years 11 months ago
A New Stereo Algorithm Integrating Luminance, Gradient and Segmentation Informations in a Belief-Propagation Framework
The paper deals with the design and implementation of a stereo algorithm. Disparity map is formulated as a Markov Random Field with a new smoothness constraint depending not only ...
Nello Balossino, Maurizio Lucenteforte, Luca Piova...
ICPR
2004
IEEE
15 years 10 months ago
Surface Sculpting with Stochastic Deformable 3D Surfaces
This paper introduces a new stochastic surface model for deformable 3D surfaces and demonstrates its utility for the purpose of 3D sculpting. This is the problem of simple-touse a...
Andrew R. Willis, Jasper Speicher, David B. Cooper
CVPR
2009
IEEE
16 years 4 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
ICPR
2008
IEEE
15 years 11 months ago
A new objective function for sequence labeling
We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
Hisashi Kashima, Yuta Tsuboi