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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 10 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
TIP
2008
133views more  TIP 2008»
13 years 6 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky
CVPR
2011
IEEE
13 years 2 months ago
Global Stereo Matching Leveraged by Sparse Ground Control Points
We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our...
Liang Wang, Ruigang Yang
ICML
2004
IEEE
14 years 7 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
ICIP
2010
IEEE
13 years 4 months ago
3D vertebrae segmentation using graph cuts with shape prior constraints
Osteoporosis is a bone disease characterized by a reduction in bone mass, resulting in an increased risk of fractures. To diagnose the osteoporosis accurately, bone mineral densit...
Melih S. Aslan, Asem M. Ali, Dongqing Chen, Ben Ar...